Download or read book Using Propensity Scores in Quasi Experimental Designs written by William M. Holmes and published by SAGE Publications. This book was released on 2013-06-10 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Using Propensity Scores in Quasi Experimental Designs written by William M. Holmes and published by SAGE Publications. This book was released on 2013-06-10 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Using Propensity Scores in Quasi experimental Designs written by William M. Holmes and published by . This book was released on 2014 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Practical Propensity Score Methods Using R written by Walter Leite and published by SAGE Publications. This book was released on 2016-10-28 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Propensity Score Analysis written by Shenyang Guo and published by SAGE. This book was released on 2015 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Quasi Experimentation written by Charles S. Reichardt and published by Guilford Publications. This book was released on 2019-09-02 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Propensity Score Analysis written by Wei Pan and published by Guilford Publications. This book was released on 2015-04-07 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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).

Download or read book Best Practices in Quantitative Methods written by Jason W. Osborne and published by SAGE. This book was released on 2008 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.

Download or read book Experimental and Quasi experimental Designs for Generalized Causal Inference written by William R. Shadish and published by Cengage Learning. This book was released on 2002 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sections include: experiments and generalised causal inference; statistical conclusion validity and internal validity; construct validity and external validity; quasi-experimental designs that either lack a control group or lack pretest observations on the outcome; quasi-experimental designs that use both control groups and pretests; quasi-experiments: interrupted time-series designs; regresssion discontinuity designs; randomised experiments: rationale, designs, and conditions conducive to doing them; practical problems 1: ethics, participation recruitment and random assignment; practical problems 2: treatment implementation and attrition; generalised causal inference: a grounded theory; generalised causal inference: methods for single studies; generalised causal inference: methods for multiple studies; a critical assessment of our assumptions.

Download or read book Causality in a Social World written by Guanglei Hong and published by John Wiley & Sons. This book was released on 2015-06-09 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Causality in a Social World introduces innovative new statistical research and strategies for investigating moderated intervention effects, mediated intervention effects, and spill-over effects using experimental or quasi-experimental data. The book uses potential outcomes to define causal effects, explains and evaluates identification assumptions using application examples, and compares innovative statistical strategies with conventional analysis methods. Whilst highlighting the crucial role of good research design and the evaluation of assumptions required for identifying causal effects in the context of each application, the author demonstrates that improved statistical procedures will greatly enhance the empirical study of causal relationship theory. Applications focus on interventions designed to improve outcomes for participants who are embedded in social settings, including families, classrooms, schools, neighbourhoods, and workplaces.

Download or read book The Encyclopedia of Research Methods in Criminology and Criminal Justice 2 Volume Set written by J. C. Barnes and published by John Wiley & Sons. This book was released on 2021-09-08 with total page 967 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Encyclopedia of RESEARCH METHODS IN CRIMINOLOGY & CRIMINAL JUSTICE The most comprehensive reference work on research designs and methods in criminology and criminal justice This Encyclopedia of Research Methods in Criminology and Criminal Justice offers a comprehensive survey of research methodologies and statistical techniques that are popular in criminology and criminal justice systems across the globe. With contributions from leading scholars and practitioners in the field, it offers a clear insight into the techniques that are currently in use to answer the pressing questions in criminology and criminal justice. The Encyclopedia contains essential information from a diverse pool of authors about research designs grounded in both qualitative and quantitative approaches. It includes information on popular datasets and leading resources of government statistics. In addition, the contributors cover a wide range of topics such as: the most current research on the link between guns and crime, rational choice theory, and the use of technology like geospatial mapping as a crime reduction tool. This invaluable reference work: Offers a comprehensive survey of international research designs, methods, and statistical techniques Includes contributions from leading figures in the field Contains data on criminology and criminal justice from Cambridge to Chicago Presents information on capital punishment, domestic violence, crime science, and much more Helps us to better understand, explain, and prevent crime Written for undergraduate students, graduate students, and researchers, The Encyclopedia of Research Methods in Criminology and Criminal Justice is the first reference work of its kind to offer a comprehensive review of this important topic.

Download or read book Developing a Protocol for Observational Comparative Effectiveness Research A User s Guide written by Agency for Health Care Research and Quality (U.S.) and published by Government Printing Office. This book was released on 2013-02-21 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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)

Download or read book Encyclopedia of Research Design written by Neil J. Salkind and published by SAGE. This book was released on 2010-06-22 with total page 1779 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases."--Publisher's description.

Download or read book Matched Sampling for Causal Effects written by Donald B. Rubin and published by Cambridge University Press. This book was released on 2006-09-04 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Mostly Harmless Econometrics written by Joshua D. Angrist and published by Princeton University Press. This book was released on 2009-01-04 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: In addition to econometric essentials, this book covers important new extensions as well as how to get standard errors right. The authors explain why fancier econometric techniques are typically unnecessary and even dangerous.

Download or read book Bridging the Evidence Gap in Obesity Prevention written by Institute of Medicine and published by National Academies Press. This book was released on 2010-12-24 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: To battle the obesity epidemic in America, health care professionals and policymakers need relevant, useful data on the effectiveness of obesity prevention policies and programs. Bridging the Evidence Gap in Obesity Prevention identifies a new approach to decision making and research on obesity prevention to use a systems perspective to gain a broader understanding of the context of obesity and the many factors that influence it.

Download or read book Targeted Learning in Data Science written by Mark J. van der Laan and published by Springer. This book was released on 2018-03-28 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook for graduate students in statistics, data science, and public health deals with the practical challenges that come with big, complex, and dynamic data. It presents a scientific roadmap to translate real-world data science applications into formal statistical estimation problems by using the general template of targeted maximum likelihood estimators. These targeted machine learning algorithms estimate quantities of interest while still providing valid inference. Targeted learning methods within data science area critical component for solving scientific problems in the modern age. The techniques can answer complex questions including optimal rules for assigning treatment based on longitudinal data with time-dependent confounding, as well as other estimands in dependent data structures, such as networks. Included in Targeted Learning in Data Science are demonstrations with soft ware packages and real data sets that present a case that targeted learning is crucial for the next generation of statisticians and data scientists. Th is book is a sequel to the first textbook on machine learning for causal inference, Targeted Learning, published in 2011. Mark van der Laan, PhD, is Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics at UC Berkeley. His research interests include statistical methods in genomics, survival analysis, censored data, machine learning, semiparametric models, causal inference, and targeted learning. Dr. van der Laan received the 2004 Mortimer Spiegelman Award, the 2005 Van Dantzig Award, the 2005 COPSS Snedecor Award, the 2005 COPSS Presidential Award, and has graduated over 40 PhD students in biostatistics and statistics. Sherri Rose, PhD, is Associate Professor of Health Care Policy (Biostatistics) at Harvard Medical School. Her work is centered on developing and integrating innovative statistical approaches to advance human health. Dr. Rose’s methodological research focuses on nonparametric machine learning for causal inference and prediction. She co-leads the Health Policy Data Science Lab and currently serves as an associate editor for the Journal of the American Statistical Association and Biostatistics.