Sibling Comparison 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 artic...

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Bibliographic Details
Published in:Annual review of statistics and its application 2022-01, Vol.9 (1), p.71-94
Main Authors: Sjölander, Arvid, Frisell, Thomas, Öberg, Sara
Format: Article
Language:English
Subjects:
between-within models
bias
causal inference
conditional effects
confounding
fixed effects models
marginal effects
Medicin och hälsovetenskap
random effects models
siblings
twins
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Summary: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.
ISSN:2326-8298
2326-831X
DOI:10.1146/annurev-statistics-040120-024521