Contents. Part 1 Introduction. Part 2 Cross-Sectional Selection Bias Adjustment

Transcription

1 From Analysis of Observational Health Care Data Using SAS. Full book available for purchase here. Contents Preface ix Part 1 Introduction Chapter 1 Introduction to Observational Studies Observational vs. Experimental Studies Issues in Observational Studies Study Design Methods Some Guidelines for Reporting Acknowledgments References Part 2 Cross-Sectional Selection Bias Adjustment Chapter 2 Propensity Score Stratification and Regression Abstract Introduction Propensity Score: Definition and Rationale Estimation of Propensity Scores Using Propensity Scores to Estimate Treatment Effects: Stratification and Regression Adjustment Evaluation of Propensity Scores Limitations and Advantages of Propensity Scores Example Summary Acknowledgments References Chapter 3 Propensity Score Matching for Estimating Treatment Effects Abstract Introduction Estimating the Propensity Score Forming Propensity Score Matched Sets Assessing Balance in Baseline Characteristics... 55

2 iv Contents 3.5 Estimating the Treatment Effect Sensitivity Analyses for Propensity Score Matching Propensity Score Matching Compared with Other Propensity Score Methods Case Study Summary Acknowledgments References Chapter 4 Doubly Robust Estimation of Treatment Effects Abstract Introduction Implemention with the DR Macro Sample Analysis Summary Conclusion References Chapter 5 Propensity Scoring with Missing Values Abstract Introduction Data Example Using SAS for IPW Estimation with Missing Values Sensitivity Analyses Discussion References Chapter 6 Instrumental Variable Method for Addressing Selection Bias Abstract Introduction Overview of Instrumental Variable Method to Control for Selection Bias Description of Case Study Traditional Ordinary Least Squares Regression Method Applied to Case Study Instrumental Variable Method Applied to Case Study Using PROC QLIM to Conduct IV Analysis Comparison to Traditional Regression Adjustment Method

3 Contents v 6.8 Discussion Conclusion Acknowledgments References Chapter 7 Local Control Approach Using JMP Abstract Introduction Some Traditional Analyses of Hypothetical Patient Registry Data The Four Phases of a Local Control Analysis Conclusion Acknowledgments Appendix: Propensity Scores and Blocking/Balancing Scores References Part 3 Longitudinal Bias Adjustment Chapter 8 A Two-Stage Longitudinal Propensity Adjustment for Analysis of Observational Data Abstract Introduction Longitudinal Model of Propensity for Treatment Longitudinal Propensity-Adjusted Treatment Effectiveness Analyses Application Summary Acknowledgments References Chapter 9 Analysis of Longitudinal Observational Data Using Marginal Structural Models Abstract Introduction MSM Methodology Example: MSM Analysis of a Simulated Schizophrenia Trial Discussion References

4 vi Contents Chapter 10 Structural Nested Models Abstract Introduction Time-Varying Causal Effect Moderation Estimation Empirical Example: Maximum Likelihood Data Analysis Using SAS PROC NLP Discussion Appendix 10.A Appendix 10.B Appendix 10.C References Chapter 11 Regression Models on Longitudinal Propensity Scores Abstract Introduction Estimation Using Regression on Longitudinal Propensity Scores Example Summary References Part 4 Claims Database Research Chapter 12 Good Research Practices for the Conduct of Observational Database Studies Abstract Introduction Checklist and Discussion Acknowledgments References Chapter 13 Dose-Response Safety Analyses Using Large Health Care Databases Abstract Introduction Data Structure Treatment Model and Censoring Model Setup Structural Model Implementation

5 Contents vii 13.5 Discussion References Part 5 Pharmacoeconomics Chapter 14 Costs and Cost-Effectiveness Analysis Using Propensity Score Bin Bootstrapping Abstract Introduction Propensity Score Bin Bootstrapping Example: Schizophrenia Effectiveness Study Discussion References Chapter 15 Incremental Net Benefit Abstract Introduction Cost-Effectiveness Analysis Parameter Estimation Example Observational Studies Discussion Acknowledgments References Chapter 16 Cost and Cost-Effectiveness Analysis with Censored Data Abstract Introduction Statistical Methods Example Discussion Acknowledgments References

6 viii Contents Part 6 Designing Observational Studies Chapter 17 Addressing Measurement and Sponsor Biases in Observational Research Abstract Introduction General Design Issues Addressing Measurement and Sponsor Bias Summary References Chapter 18 Sample Size Calculation for Observational Studies Abstract Introduction Continuous Variables Binary Variables Two-Sample Log-Rank Test for Survival Data Two-Sample Longitudinal Data Discussion Appendix: Asymptotic Distribution of Wilcoxon Rank Sum Test under H References Index From Analysis of Observational Health Care Data Using SAS by Douglas Faries, Andrew Leon, Josep Haro, and Robert Obenchain. Copyright 2010, SAS Institute Inc., Cary, North Carolina, USA. ALL RIGHTS RESERVED.