Part I Beginnings.- 1 Dilemmas and Craftsmanship.- 2 Causal Inference in Randomized Experiments.- 3 Two Simple Models for Observational Studies.- 4 Competing Theories Structure Design.- 5 Opportunities, Devices, and Instruments.- 6 Transparency.- 7 Some Counterclaims Undermine Themselves.- Part II Matching.- 8 A Matched Observational Study.- 9 Basic Tools of Multivariate Matching.- 10 Various Practical Issues in Matching.- 11 Fine Balance.- 12 Matching Without Groups.- 13 Risk-Set Matching.- 14 Matching in R.- Part III Design Sensitivity.- 15 The Power of a Sensitivity Analysis and Its Limit.- 16 Heterogeneity and Causality.- 17 Uncommon but Dramatic Responses to Treatment.- 18 Anticipated and Discovered Patterns of Response.- 19 Choice of Test Statistic.- Part IV Enhanced Design.- 20 Evidence Factors.- 21 Constructing Several Comparison Groups.- Part V Planning Analysis.- 22 After Matching, Before Analysis.- 23 Planning the Analysis.- Key Elements of Design.- Solutions to Common Problems.- Symbols.- Acronyms.- Glossary of Statistical Terms.- Further Reading.- Suggested Readings for a Course.- Index.
Paul R. Rosenbaum is the Robert G. Putzel Professor Emeritus of Statistics and Data Science at the Wharton School of the University of Pennsylvania. He is the author of Observation and Experiment: An Introduction to Causal Inference, Design of Observational Studies, Observational Studies, and Replication and Evidence Factors in Observational Studies.