A Biostatistics Toolbox for Data Analysis

Steve Selvin is a Professor of Biostatistics in the School of Public Health at University of California, Berkeley and was the head of the division from 1977 to 2004. He has published over 250 papers and authored several textbooks in the fields of biostatistics and epidemiology. His book, Survival Analysis for Epidemiologic and Medical Research, was published by Cambridge University Press in 2008.

'Professor Selvin is a master at making statistical procedures and their complex underpinnings accessible to students of all levels of expertise. This book is a brilliant compendium of Professor Selvin's tremendous understanding of the breadth and depth of biostatistical tools that he delivers to the reader with superb clarity. A broad range of salient statistical concepts are covered, pleasantly anchored with a brief history, described formally for the more initiated reader, and expertly illustrated with real-life data examples that are readily understood by the less mathematically inclined. Researchers from a myriad of scientific disciplines seeking masterful guidance about conducting their statistical data analysis will absolutely want this book at their fingertips.' Gary Shaw, Stanford University, California

• Part I. Basics: 1. Statistical distribution; 2. Confidence intervals; 3. A weighted average; 4. Two discrete probability functions; 5. Correlation; Part II. Applications: 6. The 2 x 2 table; 7. Linear bivariate regression model; 8. The 2 x k table; 9. The log-linear Poisson regression model; 10. Two-way and three-way tables analysis; 11. Bootstrap analysis; 12. Graphical analysis; 13. The variance; 14. The log-normal distribution; 15. Nonparametric analysis; Part III. Survival: 16. Rates; 17. Nonparametric survival analysis; 18. The Weibull survival function; Part IV. Epidemiology: 19. Prediction, a natural measure of performance; 20. The attributable risk summary; 21. Time/space analysis; 22. ROC curve and analysis; Part V. Genetics: 23. Selection: a statistical description; 24. Mendelian segregation analysis; 25. Admixed populations; 26. Nonrandom mating; Part VI. Theory: 27. Statistical estimation; Part VII. R-Appendix.