Salīdzināt metodes

	Sibling Fixed-Effects Design	Life-Course Epidemiology
Nozare	Social Epidemiology	Social Epidemiology
Saime	Regression model	Process / pipeline
Izcelsmes gads	2013	2002
Autors	Brian D'Onofrio, Benjamin Lahey, Eric Turkheimer & Paul Lichtenstein; Thomas Frisell et al.	Yoav Ben-Shlomo & Diana Kuh
Tips	Within-family fixed-effects design for confounding control	Conceptual and analytic framework for long-term exposure-disease modeling
Pirmavots	Frisell, T., Oberg, S., Kuja-Halkola, R., & Sjolander, A. (2012). Sibling Comparison Designs: Bias From Non-Shared Confounders and Measurement Error. Epidemiology, 23(5), 713-720.	Ben-Shlomo, Y., & Kuh, D. (2002). A life course approach to chronic disease epidemiology: conceptual models, empirical challenges and interdisciplinary perspectives. International Journal of Epidemiology, 31(2), 285-293.
Citi nosaukumi	Sibling Comparison Design, Within-Family Fixed Effects, Discordant Sibling Design, Discordant Twin Design	Life Course Approach to Chronic Disease, Life-Course Framework, Developmental Origins Epidemiology, Biological and Social Programming Approach
Saistītās	4	3
Kopsavilkums	The sibling fixed-effects, or sibling-comparison, design controls for everything that siblings share by construction. Genes (on average half), parents, household income, neighborhood, schooling, and family culture are differenced out when you compare brothers or sisters who differ in an exposure, so the residual within-family association is purged of all confounders common to the family. D'Onofrio, Lahey, Turkheimer, and Lichtenstein championed these family-based quasi-experiments as a way to integrate genetic and social-science research by rigorously testing competing causal hypotheses. Frisell and colleagues, however, gave the design its essential warning label: precisely because shared confounding is removed, the within-family estimate is unusually vulnerable to the confounders siblings do not share and to attenuation from measurement error. The design is powerful but double-edged.	Life-course epidemiology is the study of how physical and social exposures across gestation, childhood, adolescence, and adult life shape later health and disease risk. Codified by Yoav Ben-Shlomo and Diana Kuh in their 2002 International Journal of Epidemiology paper and the 2003 glossary by Kuh, Ben-Shlomo, Lynch, Hallqvist, and Power, the framework supplies a set of competing conceptual models that specify how the timing and sequence of exposures matter. Rather than asking only what causes disease, it asks when exposures act and how their effects compound. Its three signature models — critical or sensitive periods, accumulation of risk, and chains of risk — give researchers a disciplined way to translate developmental and social theory into testable longitudinal hypotheses about the origins of adult chronic disease.