Matching has become a popular approach to estimate average treatment effects. It is based on the conditional independence or unconfoundedness assumption. Checking the sensitivity of the estimated results with respect to deviations from this identifying assumption has become an increasingly...

This paper presents statistical evidence about the validity of the sibling sex ratio instrument proposed by Angrist and Evans (1998), a prominent natural “natural experiment” in the sense of Rosenzweig and Wolpin (2000). The sex ratio of the first two siblings is arguably randomly assigned...

Abstract Objectives The methods to estimate the population attributable risk (PAR) of a single risk factor or the combined PAR of multiple risk factors have been extensively studied and well developed. Ideally, the estimation of combined PAR of multiple risk factors should be based on large...

In randomized clinical trials where the effects of post-randomization factors are of interest, the standard regression analyses are biased due to unmeasured confounding. The instrumental variables (IV; Angrist et al., 1996) and G-estimation procedures under structural nested mean models (SNMMs;...

Abstract Unobserved confounding is a well-known threat to causal inference in non-experimental studies. The instrumental variable design can under certain conditions be used to recover an unbiased estimator of a treatment effect even if unobserved confounding cannot be ruled out with certainty....

Abstract The prognostic score, or disease risk score (DRS), is a summary score that is used to control for confounding in non-experimental studies. While the DRS has been shown to effectively control for measured confounders, unmeasured confounding continues to be a fundamental obstacle in...

Abstract Propensity score weighting is a tool for causal inference to adjust for measured confounders in observational studies. In practice, data often present complex structures, such as clustering, which make propensity score modeling and estimation challenging. In addition, for clustered...