Evaluates the Role of Agencies in Enhancing Education in Samagra Shiksha Abhiyan: An SEM Analysis

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This study evaluated the involvement of various agencies in enhancing education in SSA in Himachal Pradesh, focusing on infrastructure, teacher development, and community engagement. Methods: This study utilized primary data collected from stakeholders, and employed chi-square tests, confirmatory factor analysis, and structural equation modeling to analyze the relationships among observed (such as teacher training and student support programs) and latent variables (such as achievements, improvements and measures). Model fit indices, including chi-square tests, the Comparative Fit Index, the Tucker Lewis Index, the Root Mean Square Error of Approximation, the Incremental Fit Index, the Adjusted Goodness-of-Fit Index, and the Standardized Root Mean Square Residual, confirmed the adequacy of the measurement model. The analysis identified 58 variables, 26 of which were categorized as endogenous, spanning achievements, improvements, or measures. Results: The key findings highlight the effectiveness of foundational literacy and numeracy initiatives, teacher training programs and community engagement. The results demonstrate significant contributions from agencies in addressing educational challenges, with targeted interventions enhancing learning outcomes, training, system support, and feedback mechanisms. Confirmatory factor analysis and structural equation modeling validated the hypothesized relationships, indicating a strong association between infrastructure improvements and educational achievements Conclusion: This study highlights the importance of stakeholder collaboration in improving Samagra Shiksha Abhiyan. Expanding teacher training, reinforcing foundational literacy and numeracy initiatives, and programs, and encouraging active community engagement are suggested. The insights aim to guide policymakers toward inclusive rural education through focused, innovative actions. Educational Philosophy and Theory Samagra Shiksha Abhiyan Structural Equation Modeling (SEM) Teacher Development and Support Community and Parental Engagement Student Support Programs Educational Improvements Figures Figure 1 1. Introduction Education has been a cornerstone of India’s development journey, with its evolution reflecting changing socioeconomic priorities. From the ancient Gurukul system to the formulation of inclusive postindependence policies, the Indian education system has undergone significant transformations. Among the contemporary initiatives, Samagra Shiksha Abhiyan (SSA) stands out as a pivotal effort to enhance the quality and accessibility of education. Launched in 2018-19 by integrating Sarva Shiksha Abhiyan (SSA), Rashtriya Madhyamik Shiksha Abhiyan (RMSA), and Teacher Education (TE), Samagra Shiksha represents a unified approach to address educational needs from preschool to senior secondary levels. Its emphasis on equity, inclusion, and quality aligns with Sustainable Development Goal (SDG) 4, which advocates for inclusive and equitable education for all. India’s educational policies evolved significantly, beginning with the University Education Commission (1948) and the Secondary Education Commission (1952), which sought to democratize education and improve its quality. The Indian Education Commission (1964-66), led by D.S. Kothari, introduced comprehensive reforms that shaped the National Policy on Education (1968). These policies emphasized regional languages and equity and allocated 6% of national income to education (Aggarwal, 1993 ). Subsequent initiatives, such as the National Policy on Education (1986) and its revised version in 1992, addressed gaps in access and quality, particularly for marginalized groups (Ranganathan, 2007 ). The Sarva Shiksha Abhiyan (SSA) (2000–2001) aimed for universal elementary education by establishing extensive infrastructure and outreach programs, a foundation later integrated into Samagra Shiksha. The Right to Education (RTE) Act (2009) marked a milestone by making education a fundamental right for children aged 6–14 years. However, the Act's implementation faced challenges, including limited coverage beyond elementary education, inadequate provisions for girls and children with disabilities, and issues of governance (Tenth Joint Review Mission of SSA, 2009). These shortcomings underscore the importance of initiatives such as Samagra Shiksha, which adopts a more holistic and systemic approach to address such gaps. Samagra Shiksha aims to enhance learning outcomes, bridge social and gender disparities, and promote vocational and digital education. The scheme adopts a decentralized, state-specific implementation model, allowing flexibility in addressing regional priorities. Himachal Pradesh, known for its high literacy rate of 82.8% (Census 2011), exemplifies the scheme’s impact. Despite its achievements, challenges such as gender disparity persist, with female literacy at 75.93%, underscoring the need for targeted interventions. In Himachal Pradesh, the role of nongovernmental organizations (NGOs) in collaboration with the Department of Education has been instrumental in advancing Samagra Shiksha. NGOs such as Aavishkar, the Bharati Foundation, Pratham, and the Sri Aurobindo Society have contributed significantly through teacher training, community engagement, and curriculum innovations. Their partnerships, formalized through Memorandums of Understanding (MoUs), highlight the importance of multistakeholder collaboration in achieving educational objectives. India’s educational landscape is also shaped by emerging policies and initiatives such as the National Education Policy (NEP) 2020. The NEP emphasizes foundational literacy and numeracy (FLN), the integration of technology, and curriculum reforms to prepare students for the demands of the 21st century. Additionally, the Strengthening Teaching-Learning and Results for States (STARS) initiative, in partnership with the World Bank, seeks to improve educational quality by addressing systemic challenges and supporting state-level interventions. These efforts align with Samagra Shiksha’s goals of fostering an inclusive and outcome-driven education system. The implementation of Samagra Shiksha in Himachal Pradesh demonstrates the potential of collaborative efforts to improve education. With funding ratios favoring the North-Eastern and Himalayan states (90:10), the scheme leverages both state and central resources to address regional disparities. The PRABANDH system enhances monitoring and reporting, ensuring transparency and accountability in program execution. Despite these advancements, challenges persist, such as underutilized funds, disparities in resource allocation, and overemphasis on elementary education at the expense of secondary and vocational education (Khandal et al., 2023 ). Addressing these gaps requires a robust policy framework, improved governance, and sustained stakeholder engagement. In this context, the current study evaluates the implementation of Samagra Shiksha in Himachal Pradesh, focusing on the role of various agencies in infrastructure development and qualitative improvements in education. It aims to provide insights into the effectiveness of the scheme and propose actionable recommendations for policymakers and stakeholders. By leveraging a systemic approach, this study contributes to the broader discourse on creating equitable and inclusive education systems in India. 2. Methods This study employs a survey-based approach to evaluate the role of various agencies in facilitating infrastructure and services under the Samagra Shiksha Abhiyan in Himachal Pradesh. The data were collected through structured questionnaires distributed to stakeholders, including students, teachers, staff members, and parent-teacher members (PTMs), across 12 districts. A total of 450 respondents were selected using convenient sampling methods, ensuring diverse representations of the perspectives. This research investigates exogenous variables, such as teacher training, student support programs, community engagement, and early childhood education, and their influence on endogenous variables, including educational improvements, achievements, and recommended measures for enhancement. Structural equation modeling (SEM) was employed to analyze the complex relationships between these variables. SEM enables simultaneous evaluation of direct and indirect effects, providing insights into how various factors collectively contribute to educational outcomes. The use of SEM ensures a comprehensive understanding of the agencies’ impact, highlighting effective strategies and areas needing improvement. This methodological approach provides a robust framework for assessing the alignment of implemented initiatives with the goals of the Samagra Shiksha Abhiyan and offers evidence-based recommendations for enhancing educational policies and practices in Himachal Pradesh. 3. Results and Discussion The results of the structural equation modeling (SEM) analysis provide valuable insights into the adequacy of the observed model in representing the data. The fit indices, as summarized in Table 1 , demonstrate an overall acceptable model fit, with key indicators aligning closely with recommended thresholds. A chi-square value of 881.8, although statistically significant, was observed given the large sample size (n = 450). The ratio of chi-square to degrees of freedom (χ²/df = 2.263) falls within the acceptable range of < 3, indicating a reasonable fit between the model and the data. However, a goodness-of-fit index (GFI) value of 0.851 and an adjusted goodness-of-fit index (AGFI) value of 0.816, which are slightly below the ideal threshold of 0.9, meet the acceptable criterion of > 0.8, as recommended by Baumgartner and Homburg ( 1996 ). This indicates that the model adequately explains the variance covariance structure of the observed data. However, the Tucker Lewis index (TLI) (0.931) and comparative fit index (CFI) (0.924) exceeded the recommended threshold of > 0.9, reflecting a strong fit. These indices confirm the robustness of the hypothesized model and its ability to replicate the observed data. Furthermore, the root means square error of approximation (RMSEA) value of 0.068 is below the threshold of < 0.08, further supporting the adequacy of the model (Hu et al., 1999; Bentler, 1990 ; Hooper et al., 2008 ; Steiger, 2007 ). This indicates a small residual error, suggesting that the model effectively captures the relationships among the variables. However, the confirmatory factor analysis (CFA) conducted validates the constructs used in the model. The results confirm that the latent variables, defined by their observed indicators, are reliable and valid for understanding structural relationships. Table 1 Fit Indices of the Observed Model (N = 450) Model fit Acceptable level Observed Results X smaller, the better 881.8 (p = 000) χ2/df 0.8 0.851 AGFI > 0.8 0.816 RMSEA 0.9 0.931 IFI > 0.9 0.924 CFI > 0.9 0.924 Table 2 highlights the application of structural equation modeling (SEM) to analyze survey data on the effectiveness of initiatives under the Samagra Shiksha Abhiyan in Himachal Pradesh. The analysis identified 58 variables, including 26 endogenous (observed) and 32 exogenous (latent) variables, categorized into three domains: improvements, achievements, and suggested measures. The analysis revealed eight variables related to improvements, focusing on feedback and initiatives in system enhancement, resource development, and community involvement. The key contributions included teacher development programmes, technical support, content enrichment, and preprimary education initiatives. Under Achievements, eleven variables were identified, demonstrating the impact of foundational literacy and numeracy (FLN) programs. Initiatives such as the Pratham Foundation's FLN efforts and Sampark Smart Shala significantly improved foundational skills, while teacher capacity-building programmes, enhanced learning outcomes, and projects such as Aavishkar Yaatra (STEM Education) contributed to notable advancements, including success in competitive exams such as JEE and NEET. Finally, eight variables were linked to the suggested measures, emphasizing the need for improved teacher training, enriched educational content, and increased community and parental engagement. The recommendations highlighted the importance of systematic resource development and sustained technical support to ensure long-term educational improvements. Table 2 Selected AMOS Output for 3-Factor CFA Model: Summary of Model Variable and Unobserved, Exogenous Variables Variable counts (Group number 1) Number of variables in the model 58 Number of observed variables 26 Number of unobserved variables 32 Number of exogenous variables 32 Number of endogenous variables 26 A1-Foundational Literacy and Numeracy (FLN) Initiatives - A2-Early Childhood and Pre-Primary Education - A3-Student Support Programs - A4-Teacher Development and Support - A5-Student Learning and Outcomes - A6-Community and Parental Engagement - A7-Educational System Enhancement - A8-Subject-Specific Support - A9-AFeedback and Evaluations - A10-Innovations and Special Projects - I1-General Observation - I2- Focus Areas for Improvement - I3-Teacher Development and Support - I4-Student Support Programs - I5-Community and Parental Engagement - I6- Educational System Enhancement - I7-Innovations and Special Projects - I8-Feedback and Evaluations - RC1-General Observations - RC2-Teacher Development and Support - RC3-Student Support Programs - RC4-Community and Parental Engagement - RC5-Educational System Enhancement - RC6-Innovations and Special Projects - RC7-Feedback and Evaluations - RC8-Recommendations for Improvement - Unobserved, exogenous variables Achievements1 e1 e2 e4 e5 e6 Achievements2 e7 e8 e9 e10 e11 Improvement1 e12 e14 e15 e16 e17 Improvement2 e18 e19 e20 Recommendation1 e21 e22 e23 e24 Recommendation2 e25 e26 e27 e28 Table 3 summarizes the parameters analyzed in the 3-factor confirmatory factor analysis (CFA) conducted using AMOS, identifying a total of 99 parameters categorized as fixed, labeled, or unlabeled. This distribution underscores the structural complexity and analytical depth of the model. However, the fixed parameters include 32 weights, which are predetermined and not estimated during model fitting. These serve as baseline constraints and ensure model stability. However, labeled parameters, typically used for explicit estimation or interpretation, are absent, indicating a model structure that emphasizes the estimation of unlabeled parameters. Furthermore, the unmeasured parameters, totaling 67, dominate the model and include 20 weights, 15 covariances, and 32 variances. These were actively estimated during the analysis, reflecting a focus on capturing the relationships among observed and latent variables. The absence of means and intercepts within both fixed and unlabeled parameters suggests a primary emphasis on relational dynamics rather than distributional characteristics. However, in total, the model encompasses 52 weights, 15 covariances, and 32 variances, effectively representing the intricate interactions within the data. However, this parameter structure demonstrates the robustness of the CFA model in evaluating the Samagra Shiksha Abhiyan constructs, providing a strong foundation for interpreting fit indices and the underlying relationships. Table 3 Selected AMOS Output for the 3-Factor CFA Model Summary of Model Parameters Parameter Summary Weights Covariances Variances Means Intercepts Total Fixed 32 0 0 0 0 32 Labeled 0 0 0 0 0 0 Unlabeled 20 15 32 0 0 67 Total 52 15 32 0 0 99 Table 4 provides a summary of the goodness-of-fit statistics for the 3-Factor CFA model, comparing its performance with those of the saturated and independent models. The default model demonstrated an acceptable fit, supported by key indices. The CMIN/DF ratio of 3.105, while slightly exceeding the ideal threshold of 3, remains within an acceptable range for large datasets. The RMSEA value of 0.068, with a 90% confidence interval (0.063–0.074), suggested a close fit, although a p value of 0 indicated statistical significance for the RMSEA. The GFI and AGFI values of 0.851 and 0.816, respectively, met the recommended thresholds, reflecting good model adequacy. High values for the CFI (0.924), IFI (0.924), and TLI (0.913) indicate robust comparative and incremental fit. Parsimony-adjusted measures, such as the PCFI (0.807) and PNFI (0.779), further underscore the model's efficiency and balance. In contrast, the independence model showed poor fit across all indices, reinforcing the appropriateness of the default model. The Hoelter index values of 166 (p = 0.05) and 175 (p = 0.01) confirmed an adequate sample size. In summary, the indices validate the 3-factor CFA model’s ability to capture key constructs, providing a robust analytical framework for evaluating initiatives under the Samagra Shiksha Abhiyan. Table: 4 Selected AmoS Output for 3-Factor CFA Model: Goodness-of-fit statistics CMIN Model NPAR CMIN DF P CMIN/DF Default model 67 881.84 284 000 3.105 Saturated model 351 0 0 Independence model 26 8166.88 325 000 25.129 RMR, GFI Model RMR GFI AGFI PGFI Default model 0.068 0.851 0.816 0.689 Saturated model 0 1 Independence model 0.426 0.208 0.145 0.193 Baseline Comparisons Model NFI RFI IFI TLI CFI Delta1 rho1 Delta2 rho2 Default model 0.892 0.876 0.924 0.913 0.924 Saturated model 1 1 1 Independence model 0 0 0 0 0 Parsimony-Adjusted Measures Model PRATIO PNFI PCFI Default model 0.874 0.779 0.807 Saturated model 0 0 0 Independence model 1 0 0 NCP Model NCP LO 90 HI 90 Default model 597.84 512.127 691.16 Saturated model 0 0 0 Independence model 7841.88 7550.751 8139.373 FMIN Model FMIN F0 LO 90 HI 90 Default model 1.964 1.331 1.141 1.539 Saturated model 0 0 0 0 Independence model 18.189 17.465 16.817 18.128 RMSEA Model RMSEA LO 90 HI 90 PCLOSE Default model 0.068 0.063 0.074 0 Independence model 0.232 0.227 0.236 0 AIC Model AIC BCC BIC CAIC Default model 1015.84 1024.413 1291.16 1358.16 Saturated model 702 746.915 2144.346 ######## Independence model 8218.88 8222.207 8325.72 8351.72 ECVI Model ECVI LO 90 HI 90 MECVI Default model 2.262 2.072 2.47 2.282 Saturated model 1.563 1.563 1.563 1.664 Independence model 18.305 17.656 18.967 18.312 HOELTER Model HOELTER HOELTER 0.05 0.01 Default model 166 175 Independence model 21 22 RMR. GFI Figure 1 presents a structural equation modeling (SEM) path diagram for the 3-factor confirmatory factor analysis (CFA) model, which evaluates improvements, achievements, and measures within educational programs. SEM effectively explores the relationships between observed and latent variables, capturing the complexity of program dynamics. The model features latent variables (e.g., AC1, IM1, and RC1) measured by multiple observed indicators (e.g., A1–A10, I1–I8, and RC1–RC8). Strong standardized path coefficients (≥ 0.5) between latent constructs and their indicators validate the indicators’ contributions to their respective constructs. Measurement errors (e.g., e1 with a value of 0.66) highlight unexplained variances in some observed variables. Path coefficients reveal significant relationships among latent variables, such as a robust positive association (0.93) between AC1 and IM1, and weaker or inverse relationships (e.g., -0.02). Indirect effects, such as RD1 influencing multiple RC variables, indicate complex interdependencies. Bidirectional arrows reflect correlations between latent constructs, including a moderate positive correlation (0.46) between AC1 and IM1, emphasizing interconnectedness. In summary, the SEM path diagram demonstrates the model’s utility in analyzing intricate relationships in educational interventions. The findings underscore the importance of these constructs in understanding program efficacy, offering a solid basis for targeted improvements and policy development. 4. Conclusion The findings of this study underscore the efficacy and robustness of the 3-factor confirmatory factor analysis (CFA) model in evaluating the Samagra Shiksha Abhiyan initiative in Himachal Pradesh. The goodness-of-fit indices demonstrate that the model effectively captures the variance covariance structure, with key indicators such as RMSEA, CFI, and TLI meeting or exceeding recommended thresholds. Strong standardized path coefficients validate the reliability and validity of the observed indicators in measuring their respective latent constructs. The relationships between latent variables highlight significant direct and indirect effects, emphasizing the interdependence of improvements, achievements, and suggested measures in advancing educational outcomes. The analysis further identified critical contributions of improvements, such as teacher development and resource optimization, while achievements revealed tangible impacts of foundational literacy programs and STEM education initiatives. The suggested measures highlight the importance of community engagement, enriched content delivery, and systematic resource development for sustaining progress. These findings provide a comprehensive understanding of the program's effectiveness and areas for enhancement. Declarations Ethics Approval Statement: This study was conducted as part of an official project initiated and overseen by the Government of Himachal Pradesh, Department of Education. All procedures, including data collection and analysis, were carried out under the ethical clearances and administrative approval granted by the Department of Education, Government of Himachal Pradesh, which served as the competent authority for ethical oversight. Participant Consent Statement: In accordance with the protocols of the Department of Education, informed consent was obtained from all participating schools and respondents. Participation was voluntary, and confidentiality and anonymity were assured. For participants below 18 years of age, consent was obtained through school authorities acting in loco parentis, as per government guidelines. Conflicts of interest There are no conflicts of interest. Funding There was external funding for this study Acknowledgments The authors wish to express their deepest gratitude to Rajesh Sharma, IFS, State Project Director, Samagra Shiksha-STARS Project, Government of Himachal Pradesh, Shimla, for his invaluable guidance and unwavering support in facilitating the collection of the data for this study. His insights and leadership contributed significantly to the research process. We extend our heartfelt appreciation to Surender Rangta, Nodal Officer, Samagra Shiksha-STARS Project, Government of Himachal Pradesh, Shimla, for his exceptional cooperation and substantial contributions during the field investigation. His expertise and dedication were pivotal to the successful execution of this research. Our sincere thanks are also due to the dedicated staff of the Samagra Shiksha-STARS Project Directorate of Education, Lalpani, Shimla, Himachal Pradesh, whose tireless efforts and unwavering cooperation greatly facilitated the field investigation. Their assistance and support played an instrumental role in the successful completion of this study. Finally, we extend our gratitude to all the individuals and organizations who directly or indirectly contributed to this research endeavor. Their collective efforts have been invaluable in enriching this study. References Aggarwal JC (1993) Landmarks in the History of Modern Indian Education. Vikas Publishing House Pvt. Ltd. New Delhi Ranganathan S (2007) Educational Reform and Planning Challenge. Kanishka, New Delhi Tenth Joint Review Mission of Sarva Shiksha Abhiyan, GoI (2009) Aide-Memoire Khandal S, Sharma R, Gupta N (2023) Educational reforms in India: Challenges and opportunities. Int J Educ Policy Gov 14(3):45–62 Baumgartner H, Homburg C (1996) Applications of structural equation modeling in marketing and consumer research: A review. Int J Res Mark 13(2):139–161 Hu LT, Bentler PM (1999) Cutoff criteria for fit indices in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equation Modeling: Multidisciplinary J 6(1):1–55 Bentler PM (1990) Comparative fit indices in structural models. Psychol Bull 107(2):238–246 Hooper D, Coughlan J, Mullen M (2008) Structural equation modeling: Guidelines for determining model fit. Electron J Bus Res Methods 6(1):53–60 Steiger JH (2007) Understanding the limitations of global fit assessment in structural equation modeling. Pers Indiv Differ 42(5):893–898 Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7865206","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":529897319,"identity":"b160021a-c3d5-4884-a185-aa706d40d89f","order_by":0,"name":"Randhir Singh 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15:33:11","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":61589,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7865206/v1/01847108731da46d2820e572.html"},{"id":93953534,"identity":"4a8db558-770b-4398-a19e-c70866151b11","added_by":"auto","created_at":"2025-10-20 15:33:11","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":78370,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 1: 3-Factor confirmatory factor analysis model for improvements, achievements and measures in educational programs\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7865206/v1/3234a09fb1c60bdeb74e3618.jpg"},{"id":93955897,"identity":"68a27d4b-5809-4266-bd42-a150cf9ae00f","added_by":"auto","created_at":"2025-10-20 16:05:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":942069,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7865206/v1/4e9f0e6c-1d9b-42cb-8489-533998b012f5.pdf"},{"id":93954941,"identity":"bf68e7f8-f571-47e8-bef6-3bf1a02125ac","added_by":"auto","created_at":"2025-10-20 15:49:11","extension":"jpeg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":126942,"visible":true,"origin":"","legend":"\u003cp\u003eBudget Estemate\u003c/p\u003e","description":"","filename":"WhatsAppImage20251015at3.58.11PM1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7865206/v1/8efb10105b6804098ddc4e1f.jpeg"},{"id":93954693,"identity":"23bf2e84-25a9-4c98-ab50-168859b74536","added_by":"auto","created_at":"2025-10-20 15:41:11","extension":"jpeg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":187928,"visible":true,"origin":"","legend":"\u003cp\u003eLetter of approval for the funding agency\u003c/p\u003e","description":"","filename":"WhatsAppImage20251015at3.58.11PM.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7865206/v1/f81388f119eeb782bfb0547f.jpeg"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eEvaluates the Role of Agencies in Enhancing Education in Samagra Shiksha Abhiyan: An SEM Analysis\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eEducation has been a cornerstone of India\u0026rsquo;s development journey, with its evolution reflecting changing socioeconomic priorities. From the ancient Gurukul system to the formulation of inclusive postindependence policies, the Indian education system has undergone significant transformations. Among the contemporary initiatives, Samagra Shiksha Abhiyan (SSA) stands out as a pivotal effort to enhance the quality and accessibility of education. Launched in 2018-19 by integrating Sarva Shiksha Abhiyan (SSA), Rashtriya Madhyamik Shiksha Abhiyan (RMSA), and Teacher Education (TE), Samagra Shiksha represents a unified approach to address educational needs from preschool to senior secondary levels. Its emphasis on equity, inclusion, and quality aligns with Sustainable Development Goal (SDG) 4, which advocates for inclusive and equitable education for all.\u003c/p\u003e\u003cp\u003eIndia\u0026rsquo;s educational policies evolved significantly, beginning with the University Education Commission (1948) and the Secondary Education Commission (1952), which sought to democratize education and improve its quality. The Indian Education Commission (1964-66), led by D.S. Kothari, introduced comprehensive reforms that shaped the National Policy on Education (1968). These policies emphasized regional languages and equity and allocated 6% of national income to education (Aggarwal, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). Subsequent initiatives, such as the National Policy on Education (1986) and its revised version in 1992, addressed gaps in access and quality, particularly for marginalized groups (Ranganathan, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The Sarva Shiksha Abhiyan (SSA) (2000\u0026ndash;2001) aimed for universal elementary education by establishing extensive infrastructure and outreach programs, a foundation later integrated into Samagra Shiksha.\u003c/p\u003e\u003cp\u003eThe Right to Education (RTE) Act (2009) marked a milestone by making education a fundamental right for children aged 6\u0026ndash;14 years. However, the Act's implementation faced challenges, including limited coverage beyond elementary education, inadequate provisions for girls and children with disabilities, and issues of governance (Tenth Joint Review Mission of SSA, 2009). These shortcomings underscore the importance of initiatives such as Samagra Shiksha, which adopts a more holistic and systemic approach to address such gaps.\u003c/p\u003e\u003cp\u003eSamagra Shiksha aims to enhance learning outcomes, bridge social and gender disparities, and promote vocational and digital education. The scheme adopts a decentralized, state-specific implementation model, allowing flexibility in addressing regional priorities. Himachal Pradesh, known for its high literacy rate of 82.8% (Census 2011), exemplifies the scheme\u0026rsquo;s impact. Despite its achievements, challenges such as gender disparity persist, with female literacy at 75.93%, underscoring the need for targeted interventions.\u003c/p\u003e\u003cp\u003eIn Himachal Pradesh, the role of nongovernmental organizations (NGOs) in collaboration with the Department of Education has been instrumental in advancing Samagra Shiksha. NGOs such as Aavishkar, the Bharati Foundation, Pratham, and the Sri Aurobindo Society have contributed significantly through teacher training, community engagement, and curriculum innovations. Their partnerships, formalized through Memorandums of Understanding (MoUs), highlight the importance of multistakeholder collaboration in achieving educational objectives.\u003c/p\u003e\u003cp\u003eIndia\u0026rsquo;s educational landscape is also shaped by emerging policies and initiatives such as the National Education Policy (NEP) 2020. The NEP emphasizes foundational literacy and numeracy (FLN), the integration of technology, and curriculum reforms to prepare students for the demands of the 21st century. Additionally, the Strengthening Teaching-Learning and Results for States (STARS) initiative, in partnership with the World Bank, seeks to improve educational quality by addressing systemic challenges and supporting state-level interventions. These efforts align with Samagra Shiksha\u0026rsquo;s goals of fostering an inclusive and outcome-driven education system.\u003c/p\u003e\u003cp\u003eThe implementation of Samagra Shiksha in Himachal Pradesh demonstrates the potential of collaborative efforts to improve education. With funding ratios favoring the North-Eastern and Himalayan states (90:10), the scheme leverages both state and central resources to address regional disparities. The PRABANDH system enhances monitoring and reporting, ensuring transparency and accountability in program execution.\u003c/p\u003e\u003cp\u003eDespite these advancements, challenges persist, such as underutilized funds, disparities in resource allocation, and overemphasis on elementary education at the expense of secondary and vocational education (Khandal et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Addressing these gaps requires a robust policy framework, improved governance, and sustained stakeholder engagement.\u003c/p\u003e\u003cp\u003eIn this context, the current study evaluates the implementation of Samagra Shiksha in Himachal Pradesh, focusing on the role of various agencies in infrastructure development and qualitative improvements in education. It aims to provide insights into the effectiveness of the scheme and propose actionable recommendations for policymakers and stakeholders. By leveraging a systemic approach, this study contributes to the broader discourse on creating equitable and inclusive education systems in India.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003eThis study employs a survey-based approach to evaluate the role of various agencies in facilitating infrastructure and services under the Samagra Shiksha Abhiyan in Himachal Pradesh. The data were collected through structured questionnaires distributed to stakeholders, including students, teachers, staff members, and parent-teacher members (PTMs), across 12 districts. A total of 450 respondents were selected using convenient sampling methods, ensuring diverse representations of the perspectives.\u003c/p\u003e\u003cp\u003eThis research investigates exogenous variables, such as teacher training, student support programs, community engagement, and early childhood education, and their influence on endogenous variables, including educational improvements, achievements, and recommended measures for enhancement.\u003c/p\u003e\u003cp\u003eStructural equation modeling (SEM) was employed to analyze the complex relationships between these variables. SEM enables simultaneous evaluation of direct and indirect effects, providing insights into how various factors collectively contribute to educational outcomes. The use of SEM ensures a comprehensive understanding of the agencies\u0026rsquo; impact, highlighting effective strategies and areas needing improvement.\u003c/p\u003e\u003cp\u003eThis methodological approach provides a robust framework for assessing the alignment of implemented initiatives with the goals of the Samagra Shiksha Abhiyan and offers evidence-based recommendations for enhancing educational policies and practices in Himachal Pradesh.\u003c/p\u003e"},{"header":"3. Results and Discussion","content":"\u003cp\u003eThe results of the structural equation modeling (SEM) analysis provide valuable insights into the adequacy of the observed model in representing the data. The fit indices, as summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, demonstrate an overall acceptable model fit, with key indicators aligning closely with recommended thresholds. A chi-square value of 881.8, although statistically significant, was observed given the large sample size (n\u0026thinsp;=\u0026thinsp;450). The ratio of chi-square to degrees of freedom (χ\u0026sup2;/df\u0026thinsp;=\u0026thinsp;2.263) falls within the acceptable range of \u0026lt;\u0026thinsp;3, indicating a reasonable fit between the model and the data. However, a goodness-of-fit index (GFI) value of 0.851 and an adjusted goodness-of-fit index (AGFI) value of 0.816, which are slightly below the ideal threshold of 0.9, meet the acceptable criterion of \u0026gt;\u0026thinsp;0.8, as recommended by Baumgartner and Homburg (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). This indicates that the model adequately explains the variance covariance structure of the observed data. However, the Tucker Lewis index (TLI) (0.931) and comparative fit index (CFI) (0.924) exceeded the recommended threshold of \u0026gt;\u0026thinsp;0.9, reflecting a strong fit. These indices confirm the robustness of the hypothesized model and its ability to replicate the observed data. Furthermore, the root means square error of approximation (RMSEA) value of 0.068 is below the threshold of \u0026lt;\u0026thinsp;0.08, further supporting the adequacy of the model (Hu et al., 1999; Bentler, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Hooper et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Steiger, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). This indicates a small residual error, suggesting that the model effectively captures the relationships among the variables. However, the confirmatory factor analysis (CFA) conducted validates the constructs used in the model. The results confirm that the latent variables, defined by their observed indicators, are reliable and valid for understanding structural relationships.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFit Indices of the Observed Model (N\u0026thinsp;=\u0026thinsp;450)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModel fit\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAcceptable level\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eObserved Results\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esmaller, the better\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e881.8 (p\u0026thinsp;=\u0026thinsp;000)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eχ2/df\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1278.698/565\u0026thinsp;=\u0026thinsp;2.263\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGoodness-of-Fit Index (GFI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.851\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAGFI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.816\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRMSEA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.068\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTLI(NNFI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.931\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIFI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.924\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCFI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.924\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e highlights the application of structural equation modeling (SEM) to analyze survey data on the effectiveness of initiatives under the Samagra Shiksha Abhiyan in Himachal Pradesh. The analysis identified 58 variables, including 26 endogenous (observed) and 32 exogenous (latent) variables, categorized into three domains: improvements, achievements, and suggested measures.\u003c/p\u003e\u003cp\u003eThe analysis revealed eight variables related to improvements, focusing on feedback and initiatives in system enhancement, resource development, and community involvement. The key contributions included teacher development programmes, technical support, content enrichment, and preprimary education initiatives.\u003c/p\u003e\u003cp\u003eUnder Achievements, eleven variables were identified, demonstrating the impact of foundational literacy and numeracy (FLN) programs. Initiatives such as the Pratham Foundation's FLN efforts and Sampark Smart Shala significantly improved foundational skills, while teacher capacity-building programmes, enhanced learning outcomes, and projects such as Aavishkar Yaatra (STEM Education) contributed to notable advancements, including success in competitive exams such as JEE and NEET.\u003c/p\u003e\u003cp\u003eFinally, eight variables were linked to the suggested measures, emphasizing the need for improved teacher training, enriched educational content, and increased community and parental engagement. The recommendations highlighted the importance of systematic resource development and sustained technical support to ensure long-term educational improvements.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSelected AMOS Output for 3-Factor CFA Model: Summary of Model Variable and Unobserved, Exogenous Variables\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable counts (Group number 1)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of variables in the model\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e58\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of observed variables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e26\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of unobserved variables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e32\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of exogenous variables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e32\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of endogenous variables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e26\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA1-Foundational Literacy and Numeracy (FLN) Initiatives\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA2-Early Childhood and Pre-Primary Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA3-Student Support Programs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA4-Teacher Development and Support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA5-Student Learning and Outcomes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA6-Community and Parental Engagement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA7-Educational System Enhancement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA8-Subject-Specific Support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA9-AFeedback and Evaluations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA10-Innovations and Special Projects\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI1-General Observation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI2- Focus Areas for Improvement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI3-Teacher Development and Support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI4-Student Support Programs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI5-Community and Parental Engagement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI6- Educational System Enhancement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI7-Innovations and Special Projects\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI8-Feedback and Evaluations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRC1-General Observations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRC2-Teacher Development and Support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRC3-Student Support Programs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRC4-Community and Parental Engagement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRC5-Educational System Enhancement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRC6-Innovations and Special Projects\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRC7-Feedback and Evaluations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRC8-Recommendations for Improvement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eUnobserved, exogenous variables\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAchievements1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAchievements2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImprovement1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImprovement2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRecommendation1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRecommendation2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes the parameters analyzed in the 3-factor confirmatory factor analysis (CFA) conducted using AMOS, identifying a total of 99 parameters categorized as fixed, labeled, or unlabeled. This distribution underscores the structural complexity and analytical depth of the model. However, the fixed parameters include 32 weights, which are predetermined and not estimated during model fitting. These serve as baseline constraints and ensure model stability. However, labeled parameters, typically used for explicit estimation or interpretation, are absent, indicating a model structure that emphasizes the estimation of unlabeled parameters. Furthermore, the unmeasured parameters, totaling 67, dominate the model and include 20 weights, 15 covariances, and 32 variances. These were actively estimated during the analysis, reflecting a focus on capturing the relationships among observed and latent variables. The absence of means and intercepts within both fixed and unlabeled parameters suggests a primary emphasis on relational dynamics rather than distributional characteristics. However, in total, the model encompasses 52 weights, 15 covariances, and 32 variances, effectively representing the intricate interactions within the data. However, this parameter structure demonstrates the robustness of the CFA model in evaluating the Samagra Shiksha Abhiyan constructs, providing a strong foundation for interpreting fit indices and the underlying relationships.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSelected AMOS Output for the 3-Factor CFA Model Summary of Model Parameters\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter Summary\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWeights\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCovariances\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVariances\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMeans\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIntercepts\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFixed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLabeled\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnlabeled\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e67\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e52\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e15\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e32\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e99\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;4 provides a summary of the goodness-of-fit statistics for the 3-Factor CFA model, comparing its performance with those of the saturated and independent models. The default model demonstrated an acceptable fit, supported by key indices.\u003c/p\u003e\u003cp\u003eThe CMIN/DF ratio of 3.105, while slightly exceeding the ideal threshold of 3, remains within an acceptable range for large datasets. The RMSEA value of 0.068, with a 90% confidence interval (0.063\u0026ndash;0.074), suggested a close fit, although a p value of 0 indicated statistical significance for the RMSEA.\u003c/p\u003e\u003cp\u003eThe GFI and AGFI values of 0.851 and 0.816, respectively, met the recommended thresholds, reflecting good model adequacy. High values for the CFI (0.924), IFI (0.924), and TLI (0.913) indicate robust comparative and incremental fit. Parsimony-adjusted measures, such as the PCFI (0.807) and PNFI (0.779), further underscore the model's efficiency and balance.\u003c/p\u003e\u003cp\u003eIn contrast, the independence model showed poor fit across all indices, reinforcing the appropriateness of the default model. The Hoelter index values of 166 (p\u0026thinsp;=\u0026thinsp;0.05) and 175 (p\u0026thinsp;=\u0026thinsp;0.01) confirmed an adequate sample size.\u003c/p\u003e\u003cp\u003eIn summary, the indices validate the 3-factor CFA model\u0026rsquo;s ability to capture key constructs, providing a robust analytical framework for evaluating initiatives under the Samagra Shiksha Abhiyan.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTable: 4 Selected AmoS Output for 3-Factor CFA\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eModel: Goodness-of-fit statistics\u003c/b\u003e\u003c/p\u003e\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCMIN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNPAR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCMIN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCMIN/DF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eDefault model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e881.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e3.105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eSaturated model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eIndependence model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e8166.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e25.129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMR, GFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAGFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePGFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eDefault model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.816\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e0.689\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eSaturated model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eIndependence model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.426\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e0.193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline Comparisons\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 163px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTLI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eDelta1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003erho1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eDelta2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003erho2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eDefault model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.892\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.924\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e0.913\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.924\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eSaturated model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eIndependence model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParsimony-Adjusted Measures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 163px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePRATIO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePNFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eDefault model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.874\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eSaturated model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eIndependence model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNCP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 163px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNCP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLO 90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHI 90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eDefault model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e597.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e512.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e691.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eSaturated model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eIndependence model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e7841.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e7550.751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e8139.373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFMIN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 163px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFMIN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLO 90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHI 90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eDefault model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e1.964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e1.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e1.539\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eSaturated model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eIndependence model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e18.189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e17.465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e16.817\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e18.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSEA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 163px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSEA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLO 90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHI 90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCLOSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eDefault model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eIndependence model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAIC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 163px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cu\u003eAIC\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBCC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBIC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCAIC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eDefault model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e1015.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1024.413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e1291.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e1358.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eSaturated model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e746.915\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e2144.346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e########\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eIndependence model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e8218.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e8222.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e8325.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e8351.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eECVI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 163px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eECVI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLO 90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHI 90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMECVI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eDefault model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e2.262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e2.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e2.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e2.282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eSaturated model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e1.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e1.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e1.664\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eIndependence model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e18.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e17.656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e18.967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e18.312\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHOELTER\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 163px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 163px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHOELTER\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHOELTER\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eDefault model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003eIndependence model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u003cp\u003eRMR. GFI\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents a structural equation modeling (SEM) path diagram for the 3-factor confirmatory factor analysis (CFA) model, which evaluates improvements, achievements, and measures within educational programs. SEM effectively explores the relationships between observed and latent variables, capturing the complexity of program dynamics.\u003c/p\u003e\u003cp\u003eThe model features latent variables (e.g., AC1, IM1, and RC1) measured by multiple observed indicators (e.g., A1\u0026ndash;A10, I1\u0026ndash;I8, and RC1\u0026ndash;RC8). Strong standardized path coefficients (\u0026ge;\u0026thinsp;0.5) between latent constructs and their indicators validate the indicators\u0026rsquo; contributions to their respective constructs. Measurement errors (e.g., e1 with a value of 0.66) highlight unexplained variances in some observed variables.\u003c/p\u003e\u003cp\u003ePath coefficients reveal significant relationships among latent variables, such as a robust positive association (0.93) between AC1 and IM1, and weaker or inverse relationships (e.g., -0.02). Indirect effects, such as RD1 influencing multiple RC variables, indicate complex interdependencies. Bidirectional arrows reflect correlations between latent constructs, including a moderate positive correlation (0.46) between AC1 and IM1, emphasizing interconnectedness.\u003c/p\u003e\u003cp\u003eIn summary, the SEM path diagram demonstrates the model\u0026rsquo;s utility in analyzing intricate relationships in educational interventions. The findings underscore the importance of these constructs in understanding program efficacy, offering a solid basis for targeted improvements and policy development.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThe findings of this study underscore the efficacy and robustness of the 3-factor confirmatory factor analysis (CFA) model in evaluating the Samagra Shiksha Abhiyan initiative in Himachal Pradesh. The goodness-of-fit indices demonstrate that the model effectively captures the variance covariance structure, with key indicators such as RMSEA, CFI, and TLI meeting or exceeding recommended thresholds. Strong standardized path coefficients validate the reliability and validity of the observed indicators in measuring their respective latent constructs. The relationships between latent variables highlight significant direct and indirect effects, emphasizing the interdependence of improvements, achievements, and suggested measures in advancing educational outcomes.\u003c/p\u003e\u003cp\u003eThe analysis further identified critical contributions of improvements, such as teacher development and resource optimization, while achievements revealed tangible impacts of foundational literacy programs and STEM education initiatives. The suggested measures highlight the importance of community engagement, enriched content delivery, and systematic resource development for sustaining progress. These findings provide a comprehensive understanding of the program's effectiveness and areas for enhancement.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics Approval Statement: This study was conducted as part of an official project initiated and overseen by the Government of Himachal Pradesh, Department of Education. All procedures, including data collection and analysis, were carried out under the ethical clearances and administrative approval granted by the Department of Education, Government of Himachal Pradesh, which served as the competent authority for ethical oversight. Participant Consent Statement: In accordance with the protocols of the Department of Education, informed consent was obtained from all participating schools and respondents. Participation was voluntary, and confidentiality and anonymity were assured. For participants below 18 years of age, consent was obtained through school authorities acting in loco parentis, as per government guidelines.\u003c/p\u003e\u003cp\u003e\u003ch2\u003eConflicts of interest\u003c/h2\u003e\u003cp\u003eThere are no conflicts of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThere was external funding for this study\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThe authors wish to express their deepest gratitude to Rajesh Sharma, IFS, State Project Director, Samagra Shiksha-STARS Project, Government of Himachal Pradesh, Shimla, for his invaluable guidance and unwavering support in facilitating the collection of the data for this study. His insights and leadership contributed significantly to the research process.\u003c/p\u003e\u003cp\u003eWe extend our heartfelt appreciation to Surender Rangta, Nodal Officer, Samagra Shiksha-STARS Project, Government of Himachal Pradesh, Shimla, for his exceptional cooperation and substantial contributions during the field investigation. His expertise and dedication were pivotal to the successful execution of this research.\u003c/p\u003e\u003cp\u003eOur sincere thanks are also due to the dedicated staff of the Samagra Shiksha-STARS Project Directorate of Education, Lalpani, Shimla, Himachal Pradesh, whose tireless efforts and unwavering cooperation greatly facilitated the field investigation. Their assistance and support played an instrumental role in the successful completion of this study.\u003c/p\u003e\u003cp\u003eFinally, we extend our gratitude to all the individuals and organizations who directly or indirectly contributed to this research endeavor. Their collective efforts have been invaluable in enriching this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAggarwal JC (1993) Landmarks in the History of Modern Indian Education. Vikas Publishing House Pvt. Ltd. New Delhi\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRanganathan S (2007) Educational Reform and Planning Challenge. Kanishka, New Delhi\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTenth Joint Review Mission of Sarva Shiksha Abhiyan, GoI (2009) Aide-Memoire\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKhandal S, Sharma R, Gupta N (2023) Educational reforms in India: Challenges and opportunities. Int J Educ Policy Gov 14(3):45\u0026ndash;62\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaumgartner H, Homburg C (1996) Applications of structural equation modeling in marketing and consumer research: A review. Int J Res Mark 13(2):139\u0026ndash;161\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHu LT, Bentler PM (1999) Cutoff criteria for fit indices in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equation Modeling: Multidisciplinary J 6(1):1\u0026ndash;55\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBentler PM (1990) Comparative fit indices in structural models. Psychol Bull 107(2):238\u0026ndash;246\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHooper D, Coughlan J, Mullen M (2008) Structural equation modeling: Guidelines for determining model fit. Electron J Bus Res Methods 6(1):53\u0026ndash;60\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSteiger JH (2007) Understanding the limitations of global fit assessment in structural equation modeling. Pers Indiv Differ 42(5):893\u0026ndash;898\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"ecfbd712-ad89-4dfb-a7cd-ec3df277962c","identifier":"10.13039/100000179","name":"Office of the Director","awardNumber":"HPSE S- 46-Non State Actor 01/2023","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Samagra Shiksha, STAR Project, Government of Himachal Pradesh","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Samagra Shiksha Abhiyan, Structural Equation Modeling (SEM), Teacher Development and Support, Community and Parental Engagement, Student Support Programs, Educational Improvements","lastPublishedDoi":"10.21203/rs.3.rs-7865206/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7865206/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Samagra Shiksha Abhiyan (SSA) is a comprehensive programme aimed at transforming school education across India by supporting states in improving educational infrastructure and quality from preschool to senior secondary levels. This study evaluated the involvement of various agencies in enhancing education in SSA in Himachal Pradesh, focusing on infrastructure, teacher development, and community engagement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e This study utilized primary data collected from stakeholders, and employed chi-square tests, confirmatory factor analysis, and structural equation modeling to analyze the relationships among observed (such as teacher training and student support programs) and latent variables (such as achievements, improvements and measures). Model fit indices, including chi-square tests, the Comparative Fit Index, the Tucker Lewis Index, the Root Mean Square Error of Approximation, the Incremental Fit Index, the Adjusted Goodness-of-Fit Index, and the Standardized Root Mean Square Residual, confirmed the adequacy of the measurement model. The analysis identified 58 variables, 26 of which were categorized as endogenous, spanning achievements, improvements, or measures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The key findings highlight the effectiveness of foundational literacy and numeracy initiatives, teacher training programs and community engagement. The results demonstrate significant contributions from agencies in addressing educational challenges, with targeted interventions enhancing learning outcomes, training, system support, and feedback mechanisms. Confirmatory factor analysis and structural equation modeling validated the hypothesized relationships, indicating a strong association between infrastructure improvements and educational achievements\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThis study highlights the importance of stakeholder collaboration in improving Samagra Shiksha Abhiyan. Expanding teacher training, reinforcing foundational literacy and numeracy initiatives, and programs, and encouraging active community engagement are suggested. The insights aim to guide policymakers toward inclusive rural education through focused, innovative actions.\u003c/p\u003e","manuscriptTitle":"Evaluates the Role of Agencies in Enhancing Education in Samagra Shiksha Abhiyan: An SEM Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-20 15:33:06","doi":"10.21203/rs.3.rs-7865206/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"90341fd1-627f-4934-af69-1a16a73733ca","owner":[],"postedDate":"October 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56339423,"name":"Educational Philosophy and Theory"}],"tags":[],"updatedAt":"2025-10-20T15:33:06+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-20 15:33:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7865206","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7865206","identity":"rs-7865206","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}