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• W45116989 abstract "Because of population heterogeneity, causal inference with observational data in social science may suffer from two possible sources of bias: (1) bias in unobserved pretreatment factors affecting the outcome even without treatment; and (2)bias due to heterogeneity in treatment effects. Even when we control for observed covariates, these two biases may occur if the classic ignorability assumption is untrue. In cases where the ignorability assumption is true, composition bias can occur if treatment propensity is systematically associated with heterogeneous treatment effects." @default.
• W45116989 created "2016-06-24" @default.
• W45116989 creator A5049053117 @default.
• W45116989 date "2011-01-01" @default.
• W45116989 modified "2023-10-10" @default.
• W45116989 title "Causal inference and heterogeneity bias in social science" @default.
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• W45116989 doi "https://doi.org/10.3233/iks-2012-0197" @default.
• W45116989 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3747843" @default.
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