Introduction and foreword; 1. Empirical Bayes and the James-Stein estimator; 2. Large-scale hypothesis testing; 3. Significance testing algorithms; 4. False discovery rate control; 5. Local false discovery rates; 6. Theoretical, permutation and empirical null distributions; 7. Estimation accuracy; 8. Correlation questions; 9. Sets of cases (enrichment); 10. Combination, relevance, and comparability; 11. Prediction and effect size estimation; A. Exponential families; B. Programs and data sets; Bibliography; Index.