Using Propensity Scores In Quasi Experimental Designs
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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.
Using Propensity Scores In Quasi Experimental Designs
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Author : William M. Holmes
language : en
Publisher: SAGE Publications
Release Date : 2013-06-10
Using Propensity Scores In Quasi Experimental Designs written by William M. Holmes and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-10 with Social Science categories.
Using Propensity Scores in Quasi-Experimental Designs, by William M. Holmes, examines how propensity scores can be used to reduce bias with different kinds of quasi-experimental designs and to fix or improve broken experiments. Requiring minimal use of matrix and vector algebra, the book covers the causal assumptions of propensity score estimates and their many uses, linking these uses with analysis appropriate for different designs. Thorough coverage of bias assessment, propensity score estimation, and estimate improvement is provided, along with graphical and statistical methods for this process. Applications are included for analysis of variance and covariance, maximum likelihood and logistic regression, two-stage least squares, generalized linear regression, and general estimation equations. The examples use public data sets that have policy and programmatic relevance across a variety of disciplines.
Designing A Quasi Experimental Study To Test The Community College Penalty Using Propensity Score Matching Methods
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Author : Dietrich
language : en
Publisher:
Release Date : 2017
Designing A Quasi Experimental Study To Test The Community College Penalty Using Propensity Score Matching Methods written by Dietrich and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Community colleges categories.
We present a case study of the process through which a methodology was developed and applied to a quasi-experimental research study that employed propensity score matching. Methodological decisions are discussed and summarized, including an explanation of the approaches selected for each step in the study as well as rationales for these selections. Examples include identification and creation of treatment and control groups, application of relational database software and methods, calculation of propensity scores, accounting for multilevel effects, post-treatment changes and identification of post-treatment adjustment, and selection of a propensity matching algorithm. We demonstrate that much of the propensity score matching process focuses on creating a valid counterfactual or control group. Thus, propensity score matching allows researchers to focus on creating conditions that help show the impact of the treatment, rather than on other factors that may be related to the outcome of interest. Additional items discussed include decisions about missing data, use of balancing diagnostics, determination of the effect of the treatment on the outcome of interest, and sensitivity analysis. The authors propose that an appropriate methodology for such a study is best arrived at through an iterative, experimental process.
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 Mathematics 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.
Practical Propensity Score Methods Using R
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Author : Walter Leite
language : en
Publisher: SAGE Publications
Release Date : 2016-10-28
Practical Propensity Score Methods Using R written by Walter Leite and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-28 with Social Science categories.
Practical Propensity Score Methods Using R by Walter Leite is a practical book that uses a step-by-step analysis of realistic examples to help students understand the theory and code for implementing propensity score analysis with the R statistical language. With a comparison of both well-established and cutting-edge propensity score methods, the text highlights where solid guidelines exist to support best practices and where there is scarcity of research. Readers will find that this scaffolded approach to R and the book’s free online resources help them apply the text’s concepts to the analysis of their own data.
Quasi Experimentation
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Author : Charles S. Reichardt
language : en
Publisher: Guilford Publications
Release Date : 2019-09-02
Quasi Experimentation written by Charles S. Reichardt and has been published by Guilford Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-02 with Business & Economics categories.
Featuring engaging examples from diverse disciplines, this book explains how to use modern approaches to quasi-experimentation to derive credible estimates of treatment effects under the demanding constraints of field settings. Foremost expert Charles S. Reichardt provides an in-depth examination of the design and statistical analysis of pretest-posttest, nonequivalent groups, regression discontinuity, and interrupted time-series designs. He details their relative strengths and weaknesses and offers practical advice about their use. Reichardt compares quasi-experiments to randomized experiments and discusses when and why the former might be a better choice. Modern moethods for elaborating a research design to remove bias from estimates of treatment effects are described, as are tactics for dealing with missing data and noncompliance with treatment assignment. Throughout, mathematical equations are translated into words to enhance accessibility.
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.
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).
The Analysis Of Covariance And Alternatives
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Author : Bradley Huitema
language : en
Publisher: John Wiley & Sons
Release Date : 2011-10-24
The Analysis Of Covariance And Alternatives written by Bradley Huitema and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-24 with Mathematics categories.
A complete guide to cutting-edge techniques and best practices for applying covariance analysis methods The Second Edition of Analysis of Covariance and Alternatives sheds new light on its topic, offering in-depth discussions of underlying assumptions, comprehensive interpretations of results, and comparisons of distinct approaches. The book has been extensively revised and updated to feature an in-depth review of prerequisites and the latest developments in the field. The author begins with a discussion of essential topics relating to experimental design and analysis, including analysis of variance, multiple regression, effect size measures and newly developed methods of communicating statistical results. Subsequent chapters feature newly added methods for the analysis of experiments with ordered treatments, including two parametric and nonparametric monotone analyses as well as approaches based on the robust general linear model and reversed ordinal logistic regression. Four groundbreaking chapters on single-case designs introduce powerful new analyses for simple and complex single-case experiments. This Second Edition also features coverage of advanced methods including: Simple and multiple analysis of covariance using both the Fisher approach and the general linear model approach Methods to manage assumption departures, including heterogeneous slopes, nonlinear functions, dichotomous dependent variables, and covariates affected by treatments Power analysis and the application of covariance analysis to randomized-block designs, two-factor designs, pre- and post-test designs, and multiple dependent variable designs Measurement error correction and propensity score methods developed for quasi-experiments, observational studies, and uncontrolled clinical trials Thoroughly updated to reflect the growing nature of the field, Analysis of Covariance and Alternatives is a suitable book for behavioral and medical scineces courses on design of experiments and regression and the upper-undergraduate and graduate levels. It also serves as an authoritative reference work for researchers and academics in the fields of medicine, clinical trials, epidemiology, public health, sociology, and engineering.
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.