Methodologic work progressed in two areas: (1) When data are clustered, e.g. based on litter in a toxicology experiment, or sibship in a human study, conditional logistic regression is often used to allow for dependencies where inherent susceptibility to the endpoint under study varies across clusters. If there are unmeasured factors that vary across clusters and that influence susceptibility to effects of the exposure under study, then there may be residual dependency, which will invalidate such analyses. These factors are called """"""""effect modifiers"""""""" in epidemiology. We developed a statistical test for unmeasured effect modification and carried out simulations to confirm that the approach has reasonable power to detect such model violations. When such violations are detected, good alternatives exist in place of conditional logistic regression models, including the within-cluster paired resampling approach that was developed at NIEHS. (2) A number of studies have provided evidence that human fertility has declined over recent decades, raising alarm that a widespread reproductive toxicant exists in the environment. We carried out simulations to assess the bias due to recent trends in the availability of effective methods of birth control, including induced abortion, and showed that contradictory reports in the literature can potentially be explained by these demography-induced biases, and that the study of trends in fertility is particularly problematic.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Intramural Research (Z01)
Project #
1Z01ES040006-08
Application #
7007132
Study Section
(BB)
Project Start
Project End
Budget Start
Budget End
Support Year
8
Fiscal Year
2004
Total Cost
Indirect Cost
Name
U.S. National Inst of Environ Hlth Scis
Department
Type
DUNS #
City
State
Country
United States
Zip Code
Weinberg, Clarice R (2017) Invited Commentary: Can Issues With Reproducibility in Science Be Blamed on Hypothesis Testing? Am J Epidemiol 186:636-638
Lyles, Robert H; Mitchell, Emily M; Weinberg, Clarice R et al. (2016) An efficient design strategy for logistic regression using outcome- and covariate-dependent pooling of biospecimens prior to assay. Biometrics 72:965-75
Lyles, Robert H; Van Domelen, Dane; Mitchell, Emily M et al. (2015) A Discriminant Function Approach to Adjust for Processing and Measurement Error When a Biomarker is Assayed in Pooled Samples. Int J Environ Res Public Health 12:14723-40
Saha-Chaudhuri, Paramita; Umbach, David M; Weinberg, Clarice R (2011) Pooled exposure assessment for matched case-control studies. Epidemiology 22:704-12
Weinberg, C R (2009) Less is more, except when less is less: Studying joint effects. Genomics 93:10-2
Weinberg, Clarice R (2007) Can DAGs clarify effect modification? Epidemiology 18:569-72
Weinberg, Clarice R; Shore, David L; Umbach, David M et al. (2007) Using risk-based sampling to enrich cohorts for endpoints, genes, and exposures. Am J Epidemiol 166:447-55
Basso, Olga; Wilcox, Allen J; Weinberg, Clarice R (2006) Birth weight and mortality: causality or confounding? Am J Epidemiol 164:303-11
Howards, Penelope P; Hertz-Picciotto, Irva; Weinberg, Clarice R et al. (2006) Misclassification of gestational age in the study of spontaneous abortion. Am J Epidemiol 164:1126-36
Weinberg, C R (2005) Invited commentary: Barker meets Simpson. Am J Epidemiol 161:33-5; discussion 36-7

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