Kernel-based covariate functional balancing for observational studies
نویسندگان
چکیده
منابع مشابه
Methods for Improving Covariate Balance in Observational Studies
This thesis contributes to the field of causal inference, where the main interest is to estimate the effect of a treatment on some outcome. At its core, causal inference is an exercise in controlling for imbalance (differences) in covariate distributions between the treated and the controls, as such imbalances otherwise can bias estimates of causal effects. Imbalance on observed covariates can ...
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Randomization of treatment assignment in experiments generates treatment groups with approximately balanced baseline covariates. However, in observational studies, where treatment assignment is not random, patients in the active treatment and control groups often differ on crucial covariates that are related to outcomes. These covariate imbalances can lead to biased treatment effect estimates. ...
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The propensity score plays a central role in a variety of causal inference settings. In particular, matching and weighting methods based on the estimated propensity score have become increasingly common in the analysis of observational data. Despite their popularity and theoretical appeal, the main practical difficulty of these methods is that the propensity score must be estimated. Researchers...
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Family-based tests of association between a candidate locus and a disease evaluate how often a variant allele at the locus is transmitted from parents to offspring. These tests assume that in the absence of association, an affected offspring is equally likely to have inherited either one of the two homologous alleles carried by a parent. However, transmission distortion was documented in famili...
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ژورنال
عنوان ژورنال: Biometrika
سال: 2017
ISSN: 0006-3444,1464-3510
DOI: 10.1093/biomet/asx069