Statistical Causal Inferences and Their Applications in Public Health Research

Part I. Overview.- 1. Causal Inference - A Statistical Paradigm for Inferring Causality.- Part II. Propensity Score Method for Causal Inference.- 2. Overview of Propensity Score Methods.- 3. Sufficient Covariate, Propensity Variable and Doubly Robust Estimation.- 4. A Robustness Index of Propensity Score Estimation to Uncontrolled Confounders.- 5. Missing Confounder Data in Propensity Score Methods for Causal Inference.- 6. Propensity Score Modeling & Evaluation.- 7. Overcoming the Computing Barriers in Statistical Causal Inference.- Part III. Causal Inference in Randomized Clinical Studies.- 8. Semiparametric Theory and Empirical Processes in Causal Inference.- 9. Structural Nested Models for Cluster-Randomized Trials.- 10. Causal Models for Randomized Trials with Continuous Compliance.- 11. Causal Ensembles for Evaluating the Effect of Delayed Switch to Second-line Antiretroviral Regimens.- 12. Structural Functional Response Models for Complex Intervention Trials.- Part IV. Structural Equation Models for Mediation Analysis.- 13.Identification of Causal Mediation Models with An Unobserved Pre-treatment Confounder.- 14. A Comparison of Potential Outcome Approaches for Assessing Causal Mediation.- 15. Causal Mediation Analysis Using Structure Equation Models.