Organizational Structure of this Book

• Noninferiority Trials

• Dose-Finding Trials

• Pragmatic Trials

• Cluster Randomized Trials

• The Stepped-Wedge Clinical Trial

• Sample Size Calculation for a Hypothesis Test

• Minimal Clinically Important Difference

• Randomization in Clinical Trials

• Equipoise in Research

• Time-to-Event Analysis

• The “Utility” in Composite Outcome Measures

• Missing Data

• The Intention-to-Treat Principle

• Analyzing Repeated Measurements Using Mixed Models

• Logistic Regression

• Logistic Regression Diagnostics

• Number Needed to Treat

• Multiple Comparison Procedures

• Gatekeeping Strategies for Avoiding False-Positive Results in Clinical Trials With Many Comparisons

• Multiple Imputation

• Interpretation of Clinical Trials That Stopped Early

• Bayesian Analysis

• Decision Curve Analysis

• Methods for Evaluating Changes in Health Care Policy—The Difference-in-Differences Approach

Observational Studies

Study Strategy and Design

Assessment of Risk Factors and Exposures

Measurement Outcome and Analysis and Interpretation of Results

Application of Results

• Case-Control Studies

• Meta-analyses Can Be Credible and Useful

• Mendelian Randomization

• Using the E-Value to Assess the Potential Effect of Unmeasured Confounding in Observational Studies

• Confounding by Indication in Clinical Research

• Mediation Analysis

• Odds Ratios—Current Best Practice and Use

• Marginal Effects—Quantifying the Effect of Changes in Risk Factors in Logistic Regression Models

• Adjusting for Covariates

• Treatment Effects in Multicenter Randomized Clinical Trials

• The Propensity Score

• Using Free-Response Receiver Operating Characteristic Curves to Assess the Accuracy of Machine Diagnosis of Cancer

• Random-Effects Meta-analysis

• Bayesian Hierarchical Models

• Evaluating Discrimination of Risk Prediction Models

• Overview of Cost-effectiveness Analysis

• Choosing a Time Horizon in Cost and Cost-effectiveness Analysis

• On Deep Learning for Medical Image Analysis

Practical Guide to Data Sets

• 13 Articles