Journal
ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION
Volume 9, Issue -, Pages 71-94Publisher
ANNUAL REVIEWS
DOI: 10.1146/annurev-statistics-040120-024521
Keywords
between-within models; bias; causal inference; conditional effects; confounding; fixed effects models; marginal effects; random effects models; siblings; twins
Funding
- Swedish Research Council
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This article provides an extensive overview of statistical analysis methods for sibling comparison studies and discusses various methodological challenges that arise in such studies.
Unmeasured confounding is one of the main sources of bias in observational studies. A popular way to reduce confounding bias is to use sibling comparisons, which implicitly adjust for several factors in the early environment or upbringing without requiring them to be measured or known. In this article we provide a broad exposition of the statistical analysis methods for sibling comparison studies. We further discuss a number of methodological challenges that arise in sibling comparison studies.
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