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Full-Text Articles in Statistics and Probability
Semiparametric Causal Inference In Matched Cohort Studies, Edward Kennedy, Arvid Sjolander, Dylan Small
Semiparametric Causal Inference In Matched Cohort Studies, Edward Kennedy, Arvid Sjolander, Dylan Small
Edward H. Kennedy
Odds ratios can be estimated in case-control studies using standard logistic regression, ignoring the outcome-dependent sampling. In this paper we discuss an analogous result for treatment effects on the treated in matched cohort studies. Specifically, in studies where a sample of treated subjects is observed along with a separate sample of possibly matched controls, we show that efficient and doubly robust estimators of effects on the treated are computationally equivalent to standard estimators, which ignore the matching and exposure-based sampling. This is not the case for general average effects. We also show that matched cohort studies are often more efficient …
Optimal Restricted Estimation For More Efficient Longitudinal Causal Inference, Edward Kennedy, Marshall Joffe, Dylan Small
Optimal Restricted Estimation For More Efficient Longitudinal Causal Inference, Edward Kennedy, Marshall Joffe, Dylan Small
Edward H. Kennedy
Efficient semiparametric estimation of longitudinal causal effects is often analytically or computationally intractable. We propose a novel restricted estimation approach for increasing efficiency, which can be used with other techniques, is straightforward to implement, and requires no additional modeling assumptions.