,Contents
Contents
About the Book
What Does This Book Cover?
Is This Book for You?
What Should You Know about the Examples?
Software Used to Develop the Book’s Content
Example Code and Data
Acknowledgments
We Want to Hear from You
About the Authors
Chapter 1: Introduction to Observational and Real World Evidence Research
1.1 Why This Book?
1.2 Definition and Types of Real World Data (RWD)
1.3 Experimental Versus Observational Research
1.4 Types of Real World Studies
1.4.1 Cross-sectional Studies
1.4.2 Retrospective or Case-control Studies
1.4.3 Prospective or Cohort Studies
1.5 Questions Addressed by Real World Studies
1.6 The Issues: Bias and Confounding
1.6.1 Selection Bias
1.6.2 Information Bias
,1.6.3 Confounding
1.7 Guidance for Real World Research
1.8 Best Practices for Real World Research
1.9 Contents of This Book
References
Chapter 2: Causal Inference and Comparative Effectiveness: A Foundation
2.1 Introduction
2.2 Causation
2.3 From R.A. Fisher to Modern Causal Inference Analyses
2.3.1 Fisher’s Randomized Experiment
2.3.2 Neyman’s Potential Outcome Notation
2.3.3 Rubin’s Causal Model
2.3.4 Pearl’s Causal Model
2.4 Estimands
2.5 Totality of Evidence: Replication, Exploratory, and Sensitivity Analyses
2.6 Summary
References
Chapter 3: Data Examples and Simulations
3.1 Introduction
3.2 The REFLECTIONS Study
3.3 The Lindner Study
3.4 Simulations
3.5 Analysis Data Set Examples
, 3.5.1 Simulated REFLECTIONS Data
3.5.2 Simulated PCI Data
3.6 Summary
References
Chapter 4: The Propensity Score
4.1 Introduction
4.2 Estimate Propensity Score
4.2.1 Selection of Covariates
4.2.2 Address Missing Covariates Values in Estimating Propensity Score
4.2.3 Selection of Propensity Score Estimation Model
4.2.4 The Criteria of “Good” Propensity Score Estimate
4.3 Example: Estimate Propensity Scores Using the Simulated REFLECTIONS Data
4.3.1 A Priori Logistic Model
4.3.2 Automatic Logistic Model Selection
4.3.3 Boosted CART Model
4.4 Summary
References
Chapter 5: Before You Analyze – Feasibility Assessment
5.1 Introduction
5.2 Best Practices for Assessing Feasibility: Common Support
5.2.1 Walker’s Preference Score and Clinical Equipoise
5.2.2 Standardized Differences in Means and Variance Ratios
5.2.3 Tipton’s Index
Contents
About the Book
What Does This Book Cover?
Is This Book for You?
What Should You Know about the Examples?
Software Used to Develop the Book’s Content
Example Code and Data
Acknowledgments
We Want to Hear from You
About the Authors
Chapter 1: Introduction to Observational and Real World Evidence Research
1.1 Why This Book?
1.2 Definition and Types of Real World Data (RWD)
1.3 Experimental Versus Observational Research
1.4 Types of Real World Studies
1.4.1 Cross-sectional Studies
1.4.2 Retrospective or Case-control Studies
1.4.3 Prospective or Cohort Studies
1.5 Questions Addressed by Real World Studies
1.6 The Issues: Bias and Confounding
1.6.1 Selection Bias
1.6.2 Information Bias
,1.6.3 Confounding
1.7 Guidance for Real World Research
1.8 Best Practices for Real World Research
1.9 Contents of This Book
References
Chapter 2: Causal Inference and Comparative Effectiveness: A Foundation
2.1 Introduction
2.2 Causation
2.3 From R.A. Fisher to Modern Causal Inference Analyses
2.3.1 Fisher’s Randomized Experiment
2.3.2 Neyman’s Potential Outcome Notation
2.3.3 Rubin’s Causal Model
2.3.4 Pearl’s Causal Model
2.4 Estimands
2.5 Totality of Evidence: Replication, Exploratory, and Sensitivity Analyses
2.6 Summary
References
Chapter 3: Data Examples and Simulations
3.1 Introduction
3.2 The REFLECTIONS Study
3.3 The Lindner Study
3.4 Simulations
3.5 Analysis Data Set Examples
, 3.5.1 Simulated REFLECTIONS Data
3.5.2 Simulated PCI Data
3.6 Summary
References
Chapter 4: The Propensity Score
4.1 Introduction
4.2 Estimate Propensity Score
4.2.1 Selection of Covariates
4.2.2 Address Missing Covariates Values in Estimating Propensity Score
4.2.3 Selection of Propensity Score Estimation Model
4.2.4 The Criteria of “Good” Propensity Score Estimate
4.3 Example: Estimate Propensity Scores Using the Simulated REFLECTIONS Data
4.3.1 A Priori Logistic Model
4.3.2 Automatic Logistic Model Selection
4.3.3 Boosted CART Model
4.4 Summary
References
Chapter 5: Before You Analyze – Feasibility Assessment
5.1 Introduction
5.2 Best Practices for Assessing Feasibility: Common Support
5.2.1 Walker’s Preference Score and Clinical Equipoise
5.2.2 Standardized Differences in Means and Variance Ratios
5.2.3 Tipton’s Index
