{"title":"Paul R Rosenbaum","description":"","products":[{"product_id":"causal-inference-book-paul-r-rosenbaum-9780262545198","title":"Causal Inference","description":"A nontechnical guide to the basic ideas of modern causal inference, with illustrations from health, the economy, and public policy.  Which of two antiviral drugs does the most to save people infected with Ebola virus? Does a daily glass of wine prolong or shorten life? Does winning the lottery make you more or less likely to go bankrupt? How do you identify genes that cause disease? Do unions raise wages? Do some antibiotics have lethal side effects? Does the Earned Income Tax Credit help people enter the workforce?   Causal Inference provides a brief and nontechnical introduction to randomized experiments, propensity scores, natural experiments, instrumental variables, sensitivity analysis, and quasi-experimental devices. 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Observational studies are common in most fields that study the effects of treatments on people, including medicine, economics, epidemiology, education, psychology, political science and sociology. The quality and strength of evidence provided by an observational study is determined largely by its design. Design of Observational Studies is both an introduction to statistical inference in observational studies and a detailed discussion of the principles that guide the design of observational studies.      Design of Observational Studies is divided into four parts. Chapters 2, 3, and 5 of Part I cover concisely, in about one hundred pages, many of the ideas discussed in Rosenbaum’s Observational Studies (also published by Springer) but in a less technical fashion. Part II discusses the practical aspects of using propensity scores and other tools to create a matched comparison that balances many covariates. Part II includes a chapter on matching in R. In Part III, the concept of design sensitivity is used to appraise the relative ability of competing designs to distinguish treatment effects from biases due to unmeasured covariates. Part IV discusses planning the analysis of an observational study, with particular reference to Sir Ronald Fisher’s striking advice for observational studies, \"make your theories elaborate.\"      The second edition of his book, Observational Studies, was published by Springer in 2002.","brand":"WoB","offers":[{"title":"- \/ - \/ -","offer_id":51027897188625,"sku":"","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":51027900104977,"sku":"NIN9781461424864","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52522579362065,"sku":"NLS9781461424864","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1461424860.jpg?v=1751338600"},{"product_id":"design-of-observational-studies-book-paul-r-rosenbaum-9781441912121","title":"Design of Observational Studies","description":"An observational study is an empiric investigation of effects caused by treatments when randomized experimentation is unethical or infeasible. Observational studies are common in most fields that study the effects of treatments on people, including medicine, economics, epidemiology, education, psychology, political science and sociology. The quality and strength of evidence provided by an observational study is determined largely by its design. Design of Observational Studies is both an introduction to statistical inference in observational studies and a detailed discussion of the principles that guide the design of observational studies.      Design of Observational Studies is divided into four parts. Chapters 2, 3, and 5 of Part I cover concisely, in about one hundred pages, many of the ideas discussed in Rosenbaum’s Observational Studies (also published by Springer) but in a less technical fashion. Part II discusses the practical aspects of using propensity scores and other tools to create a matched comparison that balances many covariates. Part II includes a chapter on matching in R. In Part III, the concept of design sensitivity is used to appraise the relative ability of competing designs to distinguish treatment effects from biases due to unmeasured covariates. 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Observational studies are common in most fields that study the effects of treatments on people. The second edition of Observational Studies is about 50% longer than the first edition, with many new examples and methods. There are new chapters on nonadditive models for treatment effects (5) and planning observational studies     , and the chapter on coherence (9) has been extensively rewritten. Paul R. Rosenbaum is Robert G. Putzel Professor, Department of Statistics, The Wharton School of the University of Pennsylvania. 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The book is accessible to anyone who has completed an undergraduate course in mathematical statistics.  The subject is developed with the aid of two simple empirical examples concerning the health benefits or harms caused by consuming alcohol.  The data for these examples and their reanalyses are freely available in an R package, iTOS, associated with Introduction to the Theory of Observational Studies.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ GARDNERS","offer_id":52500732313873,"sku":"NGR9783031904936","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ WELL_READ \/ SBYB","offer_id":53608121172241,"sku":"CIN3031904931A","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783031904936.jpg?v=1760138774"},{"product_id":"design-of-observational-studies-book-paul-r-rosenbaum-9783030464073","title":"Design of Observational Studies","description":"This second edition of Design of Observational Studies is both an introduction to statistical inference in observational studies and a detailed discussion of the principles that guide the design of observational studies. An observational study is an empiric investigation of effects caused by treatments when randomized experimentation is unethical or infeasible. Observational studies are common in most fields that study the effects of treatments on people, including medicine, economics, epidemiology, education, psychology, political science and sociology. The quality and strength of evidence provided by an observational study is determined largely by its design.     Design of Observational Studies is organized into five parts. Chapters 2, 3, and 5 of Part I cover concisely many of the ideas discussed in Rosenbaum’s Observational Studies (also published by Springer) but in a less technical fashion. Part II discusses the practical aspects of using propensity scores and other tools to create a matched comparison that balances many covariates, and includes an updated chapter on matching in R. In Part III, the concept of design sensitivity is used to appraise the relative ability of competing designs to distinguish treatment effects from biases due to unmeasured covariates. Part IV is new to this edition; it discusses evidence factors and the computerized construction of more than one comparison group. Part V discusses planning the analysis of an observational study, with particular reference to Sir Ronald Fisher’s striking advice for observational studies: \"make your theories elaborate.\"    This new edition features updated exploration of causal influence, with four new chapters, a new R package DOS2 designed as a companion for the book, and discussion of several of the latest matching packages for R. 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