{"paper_id":"3efcba11-4c3a-4c85-80cb-d97f8b6a4fc0","body_text":"Unstable Measures, Unreliable Effects: Re-evaluating Replicability with Reliability Informed Confidence Intervals | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Unstable Measures, Unreliable Effects: Re-evaluating Replicability with Reliability Informed Confidence Intervals Carl Weems This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5937985/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Evaluating the replicability of findings in the behavioral sciences requires addressing the often-overlooked issue of measurement stability. Recent research highlights that instability is the norm for most psychological traits and behaviors. This study investigates the role of reliability of assessments and an avenue to address measurement instability with implications for replication efforts. Using measurement theory and simulated data, an adjustment to effect size confidence intervals is proposed by incorporating varying reliability estimates. Through simulations, an empirical test on data from two independent samples, and analyses on 97 effect sizes replicated in the Reproducibility Project: Psychology, Reliability-Informed Bayesian Credible Confidence Intervals (RIB CCI’s) are shown to yield more valid effect size confidence intervals. Findings highlight the critical role of reliability (i.e., measurement stability) in attenuation or inflation of effect sizes, effectively distorting expectations for replication. By integrating stability into effect size estimation, the approach offers a pathway towards more accurate research conclusions in human sciences, as well as any domain where there is inherent variability of the measurement. Social science/Psychology/Human behaviour Social science/Science, technology and society reliability stability measurement error effect size estimation Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SupplementforReliabilityPaper1202025.docx Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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