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Author: Walter Leite
Publisher: SAGE Publications
ISBN: 1483313395
Category : Social Science
Languages : en
Pages : 225
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Book Description
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.
Author: Walter Leite
Publisher: SAGE Publications
ISBN: 1483313395
Category : Social Science
Languages : en
Pages : 225
Get Book Here
Book Description
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.
Author: Walter Leite
Publisher:
ISBN: 9781071802854
Category : Quantitative research
Languages : en
Pages : 206
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Book Description
This practical book 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.
Author: Shenyang Guo
Publisher: SAGE
ISBN: 1452235007
Category : Business & Economics
Languages : en
Pages : 449
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Book Description
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.
Author: Wei Pan
Publisher: Guilford Publications
ISBN: 1462519490
Category : Psychology
Languages : en
Pages : 417
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Book Description
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).
Author: Haiyan Bai
Publisher: SAGE Publications
ISBN: 1506378064
Category : Social Science
Languages : en
Pages : 137
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Book Description
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.
Author: William M. Holmes
Publisher: SAGE Publications
ISBN: 1483310817
Category : Social Science
Languages : en
Pages : 361
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Book Description
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.
Author: Ron S. Kenett
Publisher: John Wiley & Sons
ISBN: 0470971282
Category : Mathematics
Languages : en
Pages : 533
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Book Description
Customer survey studies deals with customers, consumers and user satisfaction from a product or service. In practice, many of the customer surveys conducted by business and industry are analyzed in a very simple way, without using models or statistical methods. Typical reports include descriptive statistics and basic graphical displays. As demonstrated in this book, integrating such basic analysis with more advanced tools, provides insights on non-obvious patterns and important relationships between the survey variables. This knowledge can significantly affect the conclusions derived from a survey. Key features: Provides an integrated, case-studies based approach to analysing customer survey data. Presents a general introduction to customer surveys, within an organization’s business cycle. Contains classical techniques with modern and non standard tools. Focuses on probabilistic techniques from the area of statistics/data analysis and covers all major recent developments. Accompanied by a supporting website containing datasets and R scripts. Customer survey specialists, quality managers and market researchers will benefit from this book as well as specialists in marketing, data mining and business intelligence fields.
Author: Francisco Urdinez
Publisher: CRC Press
ISBN: 1000204510
Category : Political Science
Languages : en
Pages : 469
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Book Description
R for Political Data Science: A Practical Guide is a handbook for political scientists new to R who want to learn the most useful and common ways to interpret and analyze political data. It was written by political scientists, thinking about the many real-world problems faced in their work. The book has 16 chapters and is organized in three sections. The first, on the use of R, is for those users who are learning R or are migrating from another software. The second section, on econometric models, covers OLS, binary and survival models, panel data, and causal inference. The third section is a data science toolbox of some the most useful tools in the discipline: data imputation, fuzzy merge of large datasets, web mining, quantitative text analysis, network analysis, mapping, spatial cluster analysis, and principal component analysis. Key features: Each chapter has the most up-to-date and simple option available for each task, assuming minimal prerequisites and no previous experience in R Makes extensive use of the Tidyverse, the group of packages that has revolutionized the use of R Provides a step-by-step guide that you can replicate using your own data Includes exercises in every chapter for course use or self-study Focuses on practical-based approaches to statistical inference rather than mathematical formulae Supplemented by an R package, including all data As the title suggests, this book is highly applied in nature, and is designed as a toolbox for the reader. It can be used in methods and data science courses, at both the undergraduate and graduate levels. It will be equally useful for a university student pursuing a PhD, political consultants, or a public official, all of whom need to transform their datasets into substantive and easily interpretable conclusions.
Author: Douglas E. Faries
Publisher: SAS Press
ISBN: 9781607642275
Category : Medical care
Languages : en
Pages : 0
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Book Description
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. This book is part of the SAS Press program.
Author: Terry Elizabeth Hedrick
Publisher: SAGE Publications
ISBN: 1506319440
Category : Social Science
Languages : en
Pages : 193
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Book Description
"The Terry E. Hedrick, Leonard Bickman, and Debra J. Rog text provides a framework for designing research that is adaptable to almost any applied setting and constantly reiterates the need for establishing and maintaining credibility with the client at each level of the research process. Although the applied research book is a practical guide, suitable to accompany any thorough applied design textbook, it does a comprehensive job of presenting the distinction between basic and applied research. It introduces many topics found in the general methodology textbooks. This overlap will help students to feel comfortable in using the general skills in a more specific and complex manner." --Contemporary Psychology "For researchers needing to know how to plan and design applied research projects, Applied Research Design will be a most welcome publication. . . . The writing is clear and concise, graphics are utilized helpfully, and this book will be much appreciated by beginning social scientists who are serious but uncertain about the methodologies possible for doing applied research." --Academic Library Book Review Aimed at helping researchers and students make the transition from the classroom and the laboratory to the "real" world, the authors reveal pitfalls to avoid and strategies to undertake in order to overcome obstacles in the design and planning of applied research. Applied Research Design focuses on refining research questions when actual events force deviations from the original analysis. To accomplish this, the authors discuss how to study and monitor program implementation, statistical power analysis, and how to assess the human and material resources needed to conduct an applied research design to facilitate the management of data collection, analysis, and interpretation. Appropriate for professionals and researchers who have had some previous exposure to research methods, this book will enable the development of research strategies that are credible, useful, and--more important--feasible.
