Michael R. Chernick, PhD, is Manager of Biostatistical Services at Lankenau Institute for Medical Research, where he conducts statistical design and analysis for pharmaceutical research. He has more than thirty years of experience in the application of statistical methods to such areas as medicine, energy, engineering, insurance, and pharmaceuticals. Dr. Chernick is the author of Bootstrap Methods: A Guide for Practitioners and Researchers, Second Edition, and the coauthor of Introductory Biostatistics for the Health Sciences: Modern Applications Including Bootstrap, both published by Wiley.

"This book should be very useful for its intended readers, but it would be helpful if they had a beginning understanding of basic statistics and terminology." (Doody's, 10 February 2012)

• Preface ix 1. The What, Why, and How of Biostatistics in Medical Research 11.1 Defi nition of Statistics and Biostatistics, 11.2 Why Study Statistics?, 31.3 The Medical Literature, 91.4 Medical Research Studies, 111.4.1 Cross-sectional studies including surveys, 111.4.2 Retrospective studies, 121.4.3 Prospective studies other than clinical trials, 121.4.4 Controlled clinical trials, 121.4.5 Conclusions, 131.5 Exercises, 142. Sampling from Populations 152.1 Definitions of Populations and Samples, 172.2 Simple Random Sampling, 182.3 Selecting Simple Random Samples, 192.4 Other Sampling Methods, 272.5 Generating Bootstrap Samples, 282.6 Exercises, 323. Graphics and Summary Statistics 343.1 Continuous and Discrete Data, 343.2 Categorical Data, 353.3 Frequency Histograms, 353.4 Stem-and-Leaf Diagrams, 383.5 Box Plots, 393.6 Bar and Pie Charts, 393.7 Measures of the Center of a Distribution, 423.8 Measures of Dispersion, 463.9 Exercises, 504. Normal Distribution and Related Properties 514.1 Averages and the Central Limit Theorem, 514.2 Standard Error of the Mean, 534.3 Student's t-Distribution, 534.4 Exercises, 555. Estimating Means and Proportions 585.1 The Binomial and Poisson Distributions, 585.2 Point Estimates, 595.3 Confi dence Intervals, 625.4 Sample Size Determination, 655.5 Bootstrap Principle and Bootstrap Confidence Intervals, 665.6 Exercises, 696. Hypothesis Testing 726.1 Type I and Type II Errors, 736.2 One-Tailed and Two-Tailed Tests, 746.3 P-Values, 746.4 Comparing Means from Two Independent Samples: Two-Sample t-Test, 756.5 Paired t-Test, 766.6 Testing a Single Binomial Proportion, 786.7 Relationship Between Confi dence Intervals and Hypothesis Tests, 796.8 Sample Size Determination, 806.9 Bootstrap Tests, 816.10 Medical Diagnosis: Sensitivity and Specificity, 826.11 Special Tests in Clinical Research, 836.11.1 Superiority tests, 846.11.2 Equivalence and bioequivalence, 846.11.3 Noninferiority tests, 866.12 Repeated Measures Analysis of Variance and Longitudinal Data Analysis, 866.13 Meta-Analysis, 886.14 Exercises, 927. Correlation, Regression, and Logistic Regression 957.1 Relationship Between Two Variables and the Scatter Plot, 967.2 Pearson's Correlation, 997.3 Simple Linear Regression and Least Squares Estimation, 1017.4 Sensitivity to Outliers and Robust Regression, 1047.5 Multiple Regression, 1117.6 Logistic Regression, 1177.7 Exercises, 1228. Contingency Tables 1278.1 2 x 2 Tables and Chi-Square, 1278.2 Simpson's Paradox in the 2 x 2 Table, 1298.3 The General R x C Table, 1328.4 Fisher's Exact Test, 1338.5 Correlated Proportions and McNemar's Test, 1368.6 Relative Risk and Odds Ratio, 1388.7 Exercises, 1419. Nonparametric Methods 1459.1 Ranking Data, 1469.2 Wilcoxon Rank-Sum Test, 1469.3 Sign Test, 1499.4 Spearman's Rank-Order Correlation Coefficient, 1509.5 Insensitivity of Rank Tests to Outliers, 1539.6 Exercises, 15410. Survival Analysis 15810.1 Time-to-Event Data and Right Censoring, 15910.2 Life Tables, 16010.3 Kaplan–Meier Curves, 16410.3.1 The Kaplan-Meier curve: a nonparametric estimate of survival, 16410.3.2 Confidence intervals for the Kaplan-Meier estimate, 16510.3.3 The logrank and chi-square tests: comparing two or more survival curves, 16610.4 Parametric Survival Curves, 16810.4.1 Negative exponential survival distributions, 16810.4.2 Weibull family of survival distributions, 16910.5 Cox Proportional Hazard Models, 17010.6 Cure Rate Models, 17110.7 Exercises, 173Solutions to Selected Exercises 175Appendix: Statistical Tables 192References 204Author Index 209Subject Index 211

Michael R. Chernick, PhD, is Manager of Biostatistical Services at Lankenau Institute for Medical Research, where he conducts statistical design and analysis for pharmaceutical research. He has more than thirty years of experience in the application of statistical methods to such areas as medicine, energy, engineering, insurance, and pharmaceuticals. Dr. Chernick is the author of Bootstrap Methods: A Guide for Practitioners and Researchers, Second Edition, and the coauthor of Introductory Biostatistics for the Health Sciences: Modern Applications Including Bootstrap, both published by Wiley.

"This book should be very useful for its intended readers, but it would be helpful if they had a beginning understanding of basic statistics and terminology." (Doody's, 10 February 2012)

• Preface ix 1. The What, Why, and How of Biostatistics in Medical Research 11.1 Defi nition of Statistics and Biostatistics, 11.2 Why Study Statistics?, 31.3 The Medical Literature, 91.4 Medical Research Studies, 111.4.1 Cross-sectional studies including surveys, 111.4.2 Retrospective studies, 121.4.3 Prospective studies other than clinical trials, 121.4.4 Controlled clinical trials, 121.4.5 Conclusions, 131.5 Exercises, 142. Sampling from Populations 152.1 Definitions of Populations and Samples, 172.2 Simple Random Sampling, 182.3 Selecting Simple Random Samples, 192.4 Other Sampling Methods, 272.5 Generating Bootstrap Samples, 282.6 Exercises, 323. Graphics and Summary Statistics 343.1 Continuous and Discrete Data, 343.2 Categorical Data, 353.3 Frequency Histograms, 353.4 Stem-and-Leaf Diagrams, 383.5 Box Plots, 393.6 Bar and Pie Charts, 393.7 Measures of the Center of a Distribution, 423.8 Measures of Dispersion, 463.9 Exercises, 504. Normal Distribution and Related Properties 514.1 Averages and the Central Limit Theorem, 514.2 Standard Error of the Mean, 534.3 Student's t-Distribution, 534.4 Exercises, 555. Estimating Means and Proportions 585.1 The Binomial and Poisson Distributions, 585.2 Point Estimates, 595.3 Confi dence Intervals, 625.4 Sample Size Determination, 655.5 Bootstrap Principle and Bootstrap Confidence Intervals, 665.6 Exercises, 696. Hypothesis Testing 726.1 Type I and Type II Errors, 736.2 One-Tailed and Two-Tailed Tests, 746.3 P-Values, 746.4 Comparing Means from Two Independent Samples: Two-Sample t-Test, 756.5 Paired t-Test, 766.6 Testing a Single Binomial Proportion, 786.7 Relationship Between Confi dence Intervals and Hypothesis Tests, 796.8 Sample Size Determination, 806.9 Bootstrap Tests, 816.10 Medical Diagnosis: Sensitivity and Specificity, 826.11 Special Tests in Clinical Research, 836.11.1 Superiority tests, 846.11.2 Equivalence and bioequivalence, 846.11.3 Noninferiority tests, 866.12 Repeated Measures Analysis of Variance and Longitudinal Data Analysis, 866.13 Meta-Analysis, 886.14 Exercises, 927. Correlation, Regression, and Logistic Regression 957.1 Relationship Between Two Variables and the Scatter Plot, 967.2 Pearson's Correlation, 997.3 Simple Linear Regression and Least Squares Estimation, 1017.4 Sensitivity to Outliers and Robust Regression, 1047.5 Multiple Regression, 1117.6 Logistic Regression, 1177.7 Exercises, 1228. Contingency Tables 1278.1 2 x 2 Tables and Chi-Square, 1278.2 Simpson's Paradox in the 2 x 2 Table, 1298.3 The General R x C Table, 1328.4 Fisher's Exact Test, 1338.5 Correlated Proportions and McNemar's Test, 1368.6 Relative Risk and Odds Ratio, 1388.7 Exercises, 1419. Nonparametric Methods 1459.1 Ranking Data, 1469.2 Wilcoxon Rank-Sum Test, 1469.3 Sign Test, 1499.4 Spearman's Rank-Order Correlation Coefficient, 1509.5 Insensitivity of Rank Tests to Outliers, 1539.6 Exercises, 15410. Survival Analysis 15810.1 Time-to-Event Data and Right Censoring, 15910.2 Life Tables, 16010.3 Kaplan–Meier Curves, 16410.3.1 The Kaplan-Meier curve: a nonparametric estimate of survival, 16410.3.2 Confidence intervals for the Kaplan-Meier estimate, 16510.3.3 The logrank and chi-square tests: comparing two or more survival curves, 16610.4 Parametric Survival Curves, 16810.4.1 Negative exponential survival distributions, 16810.4.2 Weibull family of survival distributions, 16910.5 Cox Proportional Hazard Models, 17010.6 Cure Rate Models, 17110.7 Exercises, 173Solutions to Selected Exercises 175Appendix: Statistical Tables 192References 204Author Index 209Subject Index 211