Fast Facts: Medical Statistics: Understanding clinical trial results

Cover
Title Page
Copyright
Contents
List of abbreviations
Glossary
Introduction

1. Statistical inference
Endpoint types
Summary statistics
Sample and population
Hypothesis testing
Odds ratio and relative risk
Relative risk reduction and numbers needed to treat
Statistical testing

2. Analysis of time-to-event endpoints
Time to-event endpoints
Kaplan–Meier curves
Hazard ratio
Logrank test
Restricted mean survival time
Adjusting for baseline imbalances

3. Power and sample size
Type I and II errors
Controlling type I and II errors
Calculating sample size
Event-driven trials
Sample size re-evaluation

4. Multiplicity
Reducing type I errors
Hierarchical testing
Combining approaches
Subgroup evaluation

5. Interim analysis
Advantages of interim analyses
Disadvantages of interim analyses
Stopping rules for efficacy
Stopping rules for futility
The independent data monitoring committee

6. Modeling
Adjusting for baseline imbalances when comparing means
Adjusting the analysis for binary and time-to-event endpoints
Adjusting the analysis for multiple baseline factors
Assessing the dependence of outcome on baseline factors
Comparing groups while accounting for baseline imbalances
Statistical interactions
Residual variability
Statistical modeling

7. Graphical methods
Kaplan–Meier curves
Cumulative incidence curves
Forest plots
Funnel plots
Waterfall plots
Swimmer plots
Box and whisker plots
Relative risks for adverse events
Shift and trellis plots for laboratory parameters
Network geometry plots (network meta-analysis)
Index