9 citations · 59 across the 32 of their papers we have counts for
5 papers · 1 filter
Bounded, efficient and multiply robust estimation of average treatment effects using instrumental variables
Linbo Wang, Eric Tchetgen Tchetgen
Instrumental variables (IVs) are widely used for estimating causal effects in the presence of unmeasured confounding. Under the standard IV model, however, the average treatment ef…
Discrete Choice Models for Nonmonotone Nonignorable Missing Data: Identification and Inference
Eric J. Tchetgen Tchetgen, Linbo Wang, BaoLuo Sun
Nonmonotone missing data arise routinely in empirical studies of social and health sciences, and when ignored, can induce selection bias and loss of efficiency. In practice, it is…
Identification and Estimation of Causal Effects with Outcomes Truncated by Death
Linbo Wang, Xiao-Hua Zhou, Thomas S. Richardson
It is common in medical studies that the outcome of interest is truncated by death, meaning that a subject has died before the outcome could be measured. In this case, restricted a…
On falsification of the binary instrumental variable model
Linbo Wang, James M. Robins, Thomas S. Richardson
Instrumental variables are widely used for estimating causal effects in the presence of unmeasured confounding. The discrete instrumental variable model has testable implications o…
Robust Estimation of Propensity Score Weights via Subclassification
Linbo Wang, Yuexia Zhang, Thomas S. Richardson +1
Weighting estimators based on propensity scores are widely used for causal estimation in a variety of contexts, such as observational studies, marginal structural models and interf…