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Propensity Score Methods And Applications

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Propensity Score Analysis

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Author : Shenyang Guo
language : en
Publisher: SAGE Publications
Release Date : 2014-06-11

Propensity Score Analysis written by Shenyang Guo and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-11 with Social Science categories.

Fully updated to reflect the most recent changes in the field, the Second Edition of Propensity Score Analysis provides an accessible, systematic review of the origins, history, and statistical foundations of propensity score analysis, illustrating how it can be used for solving evaluation and causal-inference problems. With a strong focus on practical applications, the authors explore various strategies for employing PSA, discuss the use of PSA with alternative types of data, and delineate the limitations of PSA under a variety of constraints. Unlike existing textbooks on program evaluation and causal inference, this book delves into statistical concepts, formulas, and models within the context of a robust and engaging focus on application.

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).

Propensity Score Methods And Applications

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Author : Haiyan Bai
language : en
Publisher: SAGE Publications
Release Date : 2018-11-20

Propensity Score Methods And Applications written by Haiyan Bai and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-20 with Social Science categories.

A concise, introductory text, Propensity Score Methods and Applications describes propensity score methods (PSM) and how they are used to balance the distributions of observed covariates between treatment conditions as a means to reduce selection bias. This new QASS title specifically focuses on the procedures of implementing PSM for research in social sciences, instead of merely demonstrating the effectiveness of the method. Using succinct and approachable language to introduce the basic concepts of PSM, authors Haiyan Bai and M. H. Clark present basic concepts, assumptions, procedures, available software packages, and step-by-step examples for implementing PSM using real-world data, with exercises at the end of each chapter allowing readers to replicate examples on their own.

Using Propensity Scores In Quasi Experimental Designs

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Author : William M. Holmes
language : en
Publisher:
Release Date : 2014

Using Propensity Scores In Quasi Experimental Designs written by William M. Holmes and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Experimental design categories.

Secondary Analysis Of Electronic Health Records

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Author : MIT Critical Data
language : en
Publisher: Springer
Release Date : 2016-09-09

Secondary Analysis Of Electronic Health Records written by MIT Critical Data and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-09 with Medical categories.

This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.

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.

Developing A Protocol For Observational Comparative Effectiveness Research A User S Guide

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Author : Agency for Health Care Research and Quality (U.S.)
language : en
Publisher: Government Printing Office
Release Date : 2013-02-21

Developing A Protocol For Observational Comparative Effectiveness Research A User S Guide written by Agency for Health Care Research and Quality (U.S.) and has been published by Government Printing Office this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-21 with Medical categories.

This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov)

Propensity Score Methods And Applications

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Author : Haiyan Bai
language : en
Publisher:
Release Date : 2019

Propensity Score Methods And Applications written by Haiyan Bai and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Analysis of variance categories.

Analysis Of Observational Health Care Data Using Sas

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Author : Douglas Faries
language : en
Publisher:
Release Date : 2010-01-25

Analysis Of Observational Health Care Data Using Sas written by Douglas Faries and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-01-25 with Computers categories.

This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is sufficiently detailed to provide not only general guidance, but to help the researcher through all of the standard issues that arise in such analyses. Just enough theory is included to allow the reader to understand the pros and cons of alternative approaches and when to use each method. The numerous contributors to this book illustrate, via real-world numerical examples and SAS code, appropriate implementations of alternative methods. The end result is that researchers will learn how to present high-quality and transparent analyses that will lead to fair and objective decisions from observational data.

Propensity Score Methods And Applications

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