Uncovering selection bias in case-control studies using Bayesian post-stratification.

TitleUncovering selection bias in case-control studies using Bayesian post-stratification.
Publication TypeJournal Article
Year of Publication2013
AuthorsGeneletti S, Best N, Toledano MB, Elliott P, Richardson S
JournalStat Med
Date Published2013 Jul 10
KeywordsAdult, Bayes Theorem, Biostatistics, Case-Control Studies, Child, Electromagnetic Fields, Female, Hair Preparations, Humans, Hypospadias, Infant, Newborn, Male, Maternal Exposure, Occupational Exposure, Odds Ratio, Precursor Cell Lymphoblastic Leukemia-Lymphoma, Pregnancy, Selection Bias

Case-control studies are particularly prone to selection bias, which can affect odds ratio estimation. Approaches to discovering and adjusting for selection bias have been proposed in the literature using graphical and heuristic tools as well as more complex statistical methods. The approach we propose is based on a survey-weighting method termed Bayesian post-stratification and follows from the conditional independences that characterise selection bias. We use our approach to perform a selection bias sensitivity analysis by using ancillary data sources that describe the target case-control population to re-weight the odds ratio estimates obtained from the study. The method is applied to two case-control studies, the first investigating the association between exposure to electromagnetic fields and acute lymphoblastic leukaemia in children and the second investigating the association between maternal occupational exposure to hairspray and a congenital anomaly in male babies called hypospadias. In both case-control studies, our method showed that the odds ratios were only moderately sensitive to selection bias.

Alternate JournalStat Med
PubMed ID23303593
Grant ListG0801056 / / Medical Research Council / United Kingdom
/ / Department of Health / United Kingdom