Replication Data for: Bayesian Sensitivity Analysis for Unmeasured Confounding in Causal Panel Data Models

This is the replication file for 'Bayesian Sensitivity Analysis for Unmeasured Confounding in Causal Panel Data Models', including the package that implements the proposed method, as well as replicati

NIAID Data Ecosystem00

Replication Data for: Flexible sensitivity analysis for causal inference in observational studies subject to unmeasured confounding

R code and datasets for “Flexible sensitivity analysis for causal inference in observational studies subject to unmeasured confounding” by Lu and Ding.

NIAID Data Ecosystem10

Sensitivity Analysis via the Proportion of Unmeasured Confounding

In observational studies, identification of ATEs is generally achieved by assuming that the correct set of confounders has been measured and properly included in the relevant models. Because this assu

Taylor & Francis Group2023-05-30 更新10