- Medical Research 1. The What, Why, and How of Biostatistics in
- 1.1 Defi nition of Statistics and Biostatistics,
- 1.2 Why Study Statistics?,
- 1.3 The Medical Literature,
- 1.4 Medical Research Studies,
- 1.4.1 Cross-sectional studies including surveys,
- 1.4.2 Retrospective studies,
- 1.4.3 Prospective studies other than clinical trials,
- 1.4.4 Controlled clinical trials,
- 1.4.5 Conclusions,
- 1.5 Exercises,
- Sampling from Populations
- 2.1 Defi nitions of Populations and Samples,
- 2.2 Simple Random Sampling,
- 2.3 Selecting Simple Random Samples,
- 2.4 Other Sampling Methods,
- 2.5 Generating Bootstrap Samples,
- 2.6 Exercises,
- Sampling from Populations
- Graphics and Summary Statistics
- 3.1 Continuous and Discrete Data,
- 3.2 Categorical Data,
- 3.3 Frequency Histograms,
- 3.4 Stem-and-Leaf Diagrams,
- 3.5 Box Plots,
- 3.6 Bar and Pie Charts,
- 3.7 Measures of the Center of a Distribution,
- 3.8 Measures of Dispersion, vi Contents
- 3.9 Exercises,
- Graphics and Summary Statistics
- Normal Distribution and Related Properties
- 4.1 Averages and the Central Limit Theorem,
- 4.2 Standard Error of the Mean,
- 4.3 Student’s t-Distribution,
- 4.4 Exercises,
- Normal Distribution and Related Properties
- Estimating Means and Proportions
- 5.1 The Binomial and Poisson Distributions,
- 5.2 Point Estimates,
- 5.3 Confi dence Intervals,
- 5.4 Sample Size Determination,
- Intervals, 5.5 Bootstrap Principle and Bootstrap Confi dence
- 5.6 Exercises,
- Estimating Means and Proportions
- Hypothesis Testing
- 6.1 Type I and Type II Errors,
- 6.2 One-Tailed and Two-Tailed Tests,
- 6.3 P-Values,
- Two-Sample t-Test, 6.4 Comparing Means from Two Independent Samples:
- 6.5 Paired t-Test,
- 6.6 Testing a Single Binomial Proportion,
- Tests, 6.7 Relationship Between Confi dence Intervals and Hypothesis
- 6.8 Sample Size Determination,
- 6.9 Bootstrap Tests,
- 6.10 Medical Diagnosis: Sensitivity and Specifi city,
- 6.11 Special Tests in Clinical Research,
- 6.11.1 Superiority tests,
- 6.11.2 Equivalence and bioequivalence,
- 6.11.3 Noninferiority tests,
- Data Analysis, 6.12 Repeated Measures Analysis of Variance and Longitudinal
- 6.13 Meta-Analysis,
- 6.14 Exercises,
- Regression 7. Correlation, Regression, and Logistic
- Plot, 7.1 Relationship Between Two Variables and the Scatter
- 7.2 Pearson’s Correlation,
- Estimation, 7.3 Simple Linear Regression and Least Squares
- 7.4 Sensitivity to Outliers and Robust Regression,
- 7.5 Multiple Regression,
- 7.6 Logistic Regression,
- 7.7 Exercises,
- Regression 7. Correlation, Regression, and Logistic
- Contingency Tables
- 8.1 2 × 2 Tables and Chi-Square,
- 8.2 Simpson’s Paradox in the 2 × 2 Table,
- 8.3 The General R × C Table,
- 8.4 Fisher’s Exact Test,
- 8.5 Correlated Proportions and McNemar’s Test,
- 8.6 Relative Risk and Odds Ratio,
- 8.7 Exercises,
- Contingency Tables
- Nonparametric Methods
- 9.1 Ranking Data,
- 9.2 Wilcoxon Rank-Sum Test,
- 9.3 Sign Test,
- 9.4 Spearman’s Rank-Order Correlation Coeffi cient,
- 9.5 Insensitivity of Rank Tests to Outliers,
- 9.6 Exercises,
- Nonparametric Methods
- Hypothesis Testing
- Survival Analysis
- 10.1 Time-to-Event Data and Right Censoring,
- 10.2 Life Tables,
- 10.3 Kaplan–Meier Curves,
- of survival, 10.3.1 The Kaplan–Meier curve: a nonparametric estimate
- estimate, 10.3.2 Confi dence intervals for the Kaplan–Meier
- or more survival curves, 10.3.3 The logrank and chi-square tests: comparing two
- 10.4 Parametric Survival Curves, viii Contents
- 10.4.1 Negative exponential survival distributions,
- 10.4.2 Weibull family of survival distributions,
- 10.5 Cox Proportional Hazard Models,
- 10.6 Cure Rate Models,
- 10.7 Exercises,
- Survival Analysis
- Solutions to Selected Exercises
- Appendix: Statistical Tables
- References
- Author Index
- Subject Index
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