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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Veröffentlicht in:	Annual review of statistics and its application 2022-01, Vol.9 (1), p.71-94
Hauptverfasser:	Sjölander, Arvid, Frisell, Thomas, Öberg, Sara
Format:	Artikel
Sprache:	eng
Schlagworte:	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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Beschreibung
Zusammenfassung:	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