Empirical and parametric likelihood interval estimation for populations with many zero values: application for assessing environmental chemical concentrations and reproductive health

Kang L, Le Kang, Albert Vexler, Lili Tian, Tian L, Cooney M, Maureen Cooney, Germaine M. Buck Louis, Louis GM
Epidemiology (Cambridge, Mass.) · 2010 · doi:10.1097/EDE.0b013e3181d7eb68 · PMID:21422967
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This study developed and evaluated empirical and parametric likelihood methods for estimating confidence intervals in datasets with many zero values, applying them to compare organochlorine pesticide concentrations between women with and without endometriosis.

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This study proposes and evaluates empirical and parametric likelihood methods for estimating confidence intervals in datasets characterized by a high frequency of zero values. The researchers applied these statistical techniques to serum concentrations of two organochlorine pesticides, Aldrin and beta-Benzene hexachloride, measured in a cohort of 84 women aged 18–40 who had undergone laparoscopy. The analysis demonstrated that the proposed methods produced efficient confidence intervals, revealing no significant difference in mean pesticide concentrations between women with and without endometriosis. Relevance to endometriosis: This paper is centrally about endometriosis, as it directly compares environmental chemical exposure levels in women diagnosed with the condition versus those without it.

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Abstract

BACKGROUND: Understanding the health effects associated with environmental chemicals is challenging when individuals have concentrations at or below the laboratory limits of detection as well as when the values may round to zero or are presented in the form of 0 to substitute for missing values, which may result in many zeros in the database. Comparison of mean concentrations between individuals with and without disease necessitates estimation procedures that allow for data with many zero values. The main aim of this article is to propose and examine parametric and distribution-free methods for comparing data sets containing many zero observations. An important application of this approach is related to assessing environmental chemical concentrations and reproductive health. METHODS: We extended the empirical likelihood technique for estimating confidence intervals (CIs) in data sets with many zeros. We examined the proposed empirical likelihood interval estimations via a broad Monte Carlo study that compares the proposed method with parametric techniques. Certain characteristics of Monte Carlo simulations were chosen to be close to parameters of the real data set. We applied the method to a cohort study comprising 84 women aged 18-40 years who had undergone laparoscopy between 1999 and 2000 in whom serum concentrations of 2 organochlorine pesticides--Aldrin and beta-Benzene hexachloride (β-BHC) were measured using gas chromatography with electron capture. RESULTS: When applied to the cohort study, the method produced efficient 95% CIs, allowing for the comparison of mean serum Aldrin concentrations for women with and without endometriosis (0.000338, 0.003561) and (0.000803, 0.004211), respectively. Mean β-BHC concentrations also could be compared (0.000493, 0.005869) and (0.000680, 0.003807) based on individuals with and without the disease, respectively. Differences in mean concentrations for Aldrin and β-BHC could be estimated (-0.001563, 0.003025) and (-0.003522, 0.002890), respectively. CONCLUSIONS: We found the empirical likelihood method for estimating CIs robust when data sets contain many zeros. In so doing, mean concentrations of Aldrin or β-BHC did not differ by endometriosis diagnosis.
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Background

Understanding the health effects associated with environmental chemicals is challenging when individuals have concentrations at or below the laboratory limits of detection as well as when the values may round to zero or are presented in the form of 0 to substitute for missing values, which may result in many zeros in the database. Comparison of mean concentrations between individuals with and without disease necessitates estimation procedures that allow for data with many zero values. The main aim of this article is to propose and examine parametric and distribution-free methods for comparing data sets containing many zero observations. An important application of this approach is related to assessing environmental chemical concentrations and reproductive health.

Methods

We extended the empirical likelihood technique for estimating confidence intervals (CIs) in data sets with many zeros. We examined the proposed empirical likelihood interval estimations via a broad Monte Carlo study that compares the proposed method with parametric techniques. Certain characteristics of Monte Carlo simulations were chosen to be close to parameters of the real data set. We applied the method to a cohort study comprising 84 women aged 18–40 years who had undergone laparoscopy between 1999 and 2000 in whom serum concentrations of 2 organochlorine pesticides—Aldrin and beta-Benzene hexachloride (β-BHC) were measured using gas chromatography with electron capture.

Results

When applied to the cohort study, the method produced efficient 95% CIs, allowing for the comparison of mean serum Aldrin concentrations for women with and without endometriosis (0.000338, 0.003561) and (0.000803, 0.004211), respectively. Mean β-BHC concentrations also could be compared (0.000493, 0.005869) and (0.000680, 0.003807) based on individuals with and without the disease, respectively. Differences in mean concentrations for Aldrin and β-BHC could be estimated (−0.001563, 0.003025) and (−0.003522, 0.002890), respectively.

Conclusions

We found the empirical likelihood method for estimating CIs robust when data sets contain many zeros. In so doing, mean concentrations of Aldrin or β-BHC did not differ by endometriosis diagnosis.

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Condition tags

endometriosis

MeSH descriptors

Confidence Intervals Data Interpretation, Statistical Environmental Monitoring Likelihood Functions Reproductive Medicine Statistics, Nonparametric Adolescent Adult Aldrin Aldrin Aldrin Endometriosis Endometriosis Environmental Exposure Environmental Exposure Environmental Monitoring Epidemiological Monitoring Female Hexachlorocyclohexane Hexachlorocyclohexane

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europepmc
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pubmed
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