Statistics in Medicine

Robert H. Riffenburgh, PhD, advises on experimental design, statistical analysis, and scientific integrity of the approximately 400 concurrent studies at the Naval Medical Center San Diego. A fellow of the American Statistical Association and Royal Statistical Society, he is former Professor and Head, Statistics Department, University of Connecticut, and has been faculty at Virginia Tech., University of Hawaii, University of Maryland, University of California San Diego, San Diego State University, and University of Leiden (The Netherlands). He has been president of his own consulting firm and performed and directed operations research for the U.S. government and for NATO. He has consulted on biostatistics throughout his career, has received numerous awards, and has published more than 140 professional articles. Daniel L. Gillen, PhD, is Professor and Chair of Statistics at University of California, Irvine (UCI). He is Fellow of the American Statistical Association and Past President of the Western North American Region of the International Biometric Society. He leads the Data and Statistics Core for the Alzheimer’s Disease Research Center at UCI and is the former head of the Biostatistics Shared Resource at the UCI Chao Family Cancer Center. He serves as a consultant to the FDA and the biopharmaceutical industry and has served on over 30 independent safety monitory boards for multi-center international clinical trials. He has published over 160 peer-reviewed articles in statistical methods and clinical science journals.

1. Planning Studies: From Design to Publication 2. Planning Analysis: Addressing Your Scientific Objective 3. Probability and Relative Frequency 4. Distributions 5. Descriptive Statistics 6. Finding Probabilities 7. Hypothesis Testing: Concept and Practice 8. Confidence Intervals 9. Tests on Categorical Data 10. Risks, Odds, and ROC Curves 11. Tests of Location with Continuous Outcomes 12. Equivalence Testing 13. Tests on Variability and Distributions 14. Measuring Association and Agreement 15. Linear Regression and Correlation 16. Multiple Linear and Curvilinear Regression 17. Logistic Regression for Binary Outcomes 18. Regression Models for Count Outcomes 19. Analysis of Censored Time-To-Event Data 20. Analysis of Repeated Continuous Measures of Time 21. Sample Size Estimation 22. Clinical Trials and Group Sequential Analyses 23. Epidemiology and Alternative Sampling Designs 24. Meta Analyses 25. Bayesian Statistics 26. Questionnaires and Surveys 27. Techniques to Aid Analysis 28. Methods You Might Meet, But Not Every Day