Handbook of multiple comparisons Chapter 1. An Overview of Multiple Comparisons Xinping Cui Thorsten Dickhaus Ying Ding and Jason C. HsuChapter 2. Multiple Test Procedures Based on p ValuesAjit C. Tamhane and Jiangtao GouChapter 3. Multivariate multiple test proceduresThorsten Dickhaus Andre Neumann and Taras BodnarChapter 4. Partitioning for Confidence Sets Confident Directions and Decision PathsHelmut Finner Szu Yu Tang Xinping Cui and Jason C. HsuChapter 5. Graphical approaches for multiple comparison proceduresDong Xi and Frank BretzChapter 6. Decision Theoretic Considerations of Multiple ComparisonsArthur Cohen and Harold SackrowitzChapter 7. Identifying important predictors in large data bases multiple testing and model selectionMalgorzata Bogdan and Florian FrommletChapter 8. Prevalence EstimationJonathan D. RosenblattChapter 9. On agnostic post hoc approaches to false positive controlGiles Blanchard Pierre Neuvial and Etienne RoquainChapter 10. Group sequential and adaptive designsEkkehard Glimm and Lisa V. HampsonChapter 11. Multiple testing for dose findingFrank Bretz Dong Xi and Björn BornkampChapter 12. Multiple EndpointsBushi WangChapter 13. Subgroups Analysis for Personalized and Precision Medicine DevelopmentYi Liu Hong Tian and Jason C. HsuChapter 14. Exploratory inference: localizing relevant effects with confidenceAldo Solari and Jelle J. GoemanChapter 15. Testing SNPs in Targeted Drug DevelopmentYing Ding Yue Wei Xinjun Wang and Jason C. Hsu