Matched Sampling For Causal Effects
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Matched Sampling For Causal Effects
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Author : Donald B. Rubin
language : en
Publisher:
Release Date : 2006
Matched Sampling For Causal Effects written by Donald B. Rubin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Sampling (Statistics) categories.
This selection of Donald B. Rubin's contributions to matched sampling includes classic theoretical studies as well as real applications. Each of the seven parts has an introduction by the author offering historical and current context. The book thus provides an accessible introduction to the study of matched sampling for readers across the statistical, social, and medical sciences.
Matched Sampling For Causal Effects
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Author : Donald B. Rubin
language : en
Publisher: Cambridge University Press
Release Date : 2006-09-04
Matched Sampling For Causal Effects written by Donald B. Rubin and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-04 with Mathematics categories.
Matched sampling is often used to help assess the causal effect of some exposure or intervention, typically when randomized experiments are not available or cannot be conducted. This book presents a selection of Donald B. Rubin's research articles on matched sampling, from the early 1970s, when the author was one of the major researchers involved in establishing the field, to recent contributions to this now extremely active area. The articles include fundamental theoretical studies that have become classics, important extensions, and real applications that range from breast cancer treatments to tobacco litigation to studies of criminal tendencies. They are organized into seven parts, each with an introduction by the author that provides historical and personal context and discusses the relevance of the work today. A concluding essay offers advice to investigators designing observational studies. The book provides an accessible introduction to the study of matched sampling and will be an indispensable reference for students and researchers.
Causal Inference For Case Control Studies
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Author : Sherri Rose
language : en
Publisher:
Release Date : 2011
Causal Inference For Case Control Studies written by Sherri Rose and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Case-control study designs are frequently used in public health and medical research to assess potential risk factors for disease. These study designs are particularly attractive to investigators researching rare diseases, as they are able to sample known cases of disease, vs. following a large number of subjects and waiting for disease onset in a relatively small number of individuals. The data-generating experiment in case-control study designs involves an additional complexity called biased sampling. That is, one assumes the underlying experiment that randomly samples a unit from a target population, measures baseline characteristics, assigns an exposure, and measures a final binary outcome, but one samples from the conditional probability distribution, given the value of the binary outcome. One still desires to assess the causal effect of exposure on the binary outcome for the target population. The targeted maximum likelihood estimator of a causal effect of treatment on the binary outcome based on such case-control studies is presented. Our proposed case-control-weighted targeted maximum likelihood estimator for case-control studies relies on knowledge of the true prevalence probability, or a reasonable estimate of this probability, to eliminate the bias of the case-control sampling design. We use the prevalence probability in case-control weights, and our case-control weighting scheme successfully maps the targeted maximum likelihood estimator for a random sample into a method for case-control sampling. Individually matched case-control study designs are commonly implemented in the field of public health. While matching is intended to eliminate confounding, the main potential benefit of matching in case-control studies is a gain in efficiency. We investigate the use of the case-control-weighted targeted maximum likelihood estimator to estimate causal effects in matched case-control study designs. We also compare the case-control-weighted targeted maximum likelihood estimator in matched and unmatched designs in an effort to determine which design yields the most information about the causal effect. In many practical situations where a causal effect is the parameter of interest, researchers may be better served using an unmatched design. We also consider two-stage sampling designs, including so-called nested case-control studies, where one takes a random sample from a target population and completes measurements on each subject in the first stage. The second stage involves drawing a subsample from the original sample, collecting additional data on the subsample. This data structure can be viewed as a missing data structure on the full-data structure collected in the second stage of the study. We propose an inverse-probability-of-censoring-weighted targeted maximum likelihood estimator in two-stage sampling designs. Two-stage designs are also common for prediction research questions. We present an analysis using super learner in nested case-control data from a large Kaiser Permanente database to generate a function for mortality risk prediction.
Propensity Score Analysis
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Author : Wei Pan
language : en
Publisher: Guilford Publications
Release Date : 2015-04-07
Propensity Score Analysis written by Wei Pan and has been published by Guilford Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-07 with Psychology categories.
This book is designed to help researchers better design and analyze observational data from quasi-experimental studies and improve the validity of research on causal claims. It provides clear guidance on the use of different propensity score analysis (PSA) methods, from the fundamentals to complex, cutting-edge techniques. Experts in the field introduce underlying concepts and current issues and review relevant software programs for PSA. The book addresses the steps in propensity score estimation, including the use of generalized boosted models, how to identify which matching methods work best with specific types of data, and the evaluation of balance results on key background covariates after matching. Also covered are applications of PSA with complex data, working with missing data, controlling for unobserved confounding, and the extension of PSA to prognostic score analysis for causal inference. User-friendly features include statistical program codes and application examples. Data and software code for the examples are available at the companion website (www.guilford.com/pan-materials).
Microeconometrics
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Author : Steven Durlauf
language : en
Publisher: Springer
Release Date : 2016-06-07
Microeconometrics written by Steven Durlauf and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-07 with Literary Criticism categories.
Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.
Propensity Score Analysis
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Author : Shenyang Guo
language : en
Publisher: SAGE
Release Date : 2015
Propensity Score Analysis written by Shenyang Guo and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Business & Economics categories.
Provides readers with a systematic review of the origins, history, and statistical foundations of Propensity Score Analysis (PSA) and illustrates how it can be used for solving evaluation and causal-inference problems.
Handbook Of Matching And Weighting Adjustments For Causal Inference
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Author : José R. Zubizarreta
language : en
Publisher: CRC Press
Release Date : 2023-04-11
Handbook Of Matching And Weighting Adjustments For Causal Inference written by José R. Zubizarreta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-11 with Mathematics categories.
An observational study infers the effects caused by a treatment, policy, program, intervention, or exposure in a context in which randomized experimentation is unethical or impractical. One task in an observational study is to adjust for visible pretreatment differences between the treated and control groups. Multivariate matching and weighting are two modern forms of adjustment. This handbook provides a comprehensive survey of the most recent methods of adjustment by matching, weighting, machine learning and their combinations. Three additional chapters introduce the steps from association to causation that follow after adjustments are complete. When used alone, matching and weighting do not use outcome information, so they are part of the design of an observational study. When used in conjunction with models for the outcome, matching and weighting may enhance the robustness of model-based adjustments. The book is for researchers in medicine, economics, public health, psychology, epidemiology, public program evaluation, and statistics who examine evidence of the effects on human beings of treatments, policies or exposures.
The Central Role Of The Propensity Score In Observational Studies For Causal Effects
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Author : Paul R. Rosenbaum
language : en
Publisher:
Release Date : 1982
The Central Role Of The Propensity Score In Observational Studies For Causal Effects written by Paul R. Rosenbaum and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982 with Analysis of Covariance categories.
The results of observational studies are often disputed because of nonrandom treatment assignment. For example, patients at greater risk may be overrepresented in some treatment group. This paper discusses the central role of propensity scores and balancing scores in the analysis of observational studies. The propensity score is the (estimated) conditional probability of assignment to a particular treatment given a vector of observed covariates. Both large and small sample theory show that adjustment for the scalar propensity score is sufficient to remove bias due to all observed covariates. Applications include: matched sampling on the univariate propensity score which is equal percent bias reducing under more general conditions than required for discriminant matching, multivariate adjustment by subclassification on balancing scores where the same subclasses are used to estimate treatment effects for all outcome variables and in all subpopulations, and visual representation of multivariate adjustment by a two-dimensional plot. (Author).
Design Of Observational Studies
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Author : Paul R. Rosenbaum
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-10-22
Design Of Observational Studies written by Paul R. Rosenbaum and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-10-22 with Mathematics categories.
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. 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.
The Reviewer S Guide To Quantitative Methods In The Social Sciences
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Author : Gregory R. Hancock
language : en
Publisher: Routledge
Release Date : 2010-04-26
The Reviewer S Guide To Quantitative Methods In The Social Sciences written by Gregory R. Hancock and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-04-26 with Education categories.
Designed for reviewers of research manuscripts and proposals in the social and behavioral sciences, and beyond, this title includes chapters that address traditional and emerging quantitative methods of data analysis.