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Statistical Models For The Social And Behavioral Sciences
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Book Synopsis Handbook of Statistical Modeling for the Social and Behavioral Sciences by : G. Arminger
Download or read book Handbook of Statistical Modeling for the Social and Behavioral Sciences written by G. Arminger and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 603 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contributors thoroughly survey the most important statistical models used in empirical reserch in the social and behavioral sciences. Following a common format, each chapter introduces a model, illustrates the types of problems and data for which the model is best used, provides numerous examples that draw upon familiar models or procedures, and includes material on software that can be used to estimate the models studied. This handbook will aid researchers, methodologists, graduate students, and statisticians to understand and resolve common modeling problems.
Book Synopsis Statistical Methods for the Social and Behavioural Sciences by : David B. Flora
Download or read book Statistical Methods for the Social and Behavioural Sciences written by David B. Flora and published by SAGE. This book was released on 2017-12-11 with total page 769 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical methods in modern research increasingly entail developing, estimating and testing models for data. Rather than rigid methods of data analysis, the need today is for more flexible methods for modelling data. In this logical, easy-to-follow and exceptionally clear book, David Flora provides a comprehensive survey of the major statistical procedures currently used. His innovative model-based approach teaches you how to: Understand and choose the right statistical model to fit your data Match substantive theory and statistical models Apply statistical procedures hands-on, with example data analyses Develop and use graphs to understand data and fit models to data Work with statistical modeling principles using any software package Learn by applying, with input and output files for R, SAS, SPSS, and Mplus. Statistical Methods for the Social and Behavioural Sciences: A Model Based Approach is the essential guide for those looking to extend their understanding of the principles of statistics, and begin using the right statistical modeling method for their own data. It is particularly suited to second or advanced courses in statistical methods across the social and behavioural sciences.
Book Synopsis Statistical Models for the Social and Behavioral Sciences by : William H. Crown
Download or read book Statistical Models for the Social and Behavioral Sciences written by William H. Crown and published by Praeger. This book was released on 1998-02-18 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple regression analysis has been widely used by researchers to analyze complex social problems since the 1950s. A specialization in economics, known as econometrics, developed out of a recognition that multiple regression is based upon a large number of assumptions—many of which are commonly violated in specific applications. Econometricians developed tests for violations of the regression model assumptions, as well as a variety of corrective measures for estimating regression models in the presence of many of the violations. Unfortunately, the mathematical sophistication required to understand the econometrics literature started out high and has continued to rise over the years. As a consequence, an understanding of the assumptions of the regression model, tests for violations, and corrective estimation approaches have failed to permeate widely many other policy-related disciplines such as political science, social work, public administration, and sociology. One of the key objectives of this book is to translate the results from the econometrics literature into language that policy analysts from other disciplines can understand easily. A second objective is to present a discussion of so-called limited-dependent variable models. One of the assumptions of the regression model is that the dependent variable is measured on an interval scale. But often the dependent variable of interest is discrete or categorical. Whether someone is in poverty or, whether they are working full-time, part-time, or out of the labor force, marital status—all are examples of categorical variables that might be of policy interest. Moreover, the growing availability of large-scale public use data sets containing information on individuals and families has heightened the relevance of categorical variables in policy analysis. The mathematical preparation required to understand procedures for estimating categorical models is, however, even more daunting than that for fully understanding and using the regression model. As with the theoretical development of the regression model, most presentations of categorical models, such as Logit and Probit, are to be found in econometric literature. Moreover, this literature offers little in the way of practical advice on how to estimate and interpret model results. This book is the first to present a detailed and accessible discussion of multiple regression and limited-dependent variable models in the context of policy analysis. As such it will be an invaluable resource for most scholars, researchers, and students in the social and behavioral sciences.
Book Synopsis Statistical Models for the Social and Behavioral Sciences by : James H. Dwyer
Download or read book Statistical Models for the Social and Behavioral Sciences written by James H. Dwyer and published by Oxford University Press, USA. This book was released on 1983 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: This pathbreaking graduate text in quantitative methodology attempts to provide a solution to a number of problems which have confronted empirical social science throughout its history -- the general overload of statistics and the apparents distinction between methods appropriate for analysis of variance and those appropriate for analysis of quasi-experiments -- proposing a linear model as the general and unified statistical model applicable to a full range of experimental designs. "An extremely sensible and usable step beyond its competitors. I will strongly recommend it to my students." --Steven Penrod, University of Wisconsin. "Deserves a place on that small shelf of valuable references for knowledgeable causal researchers." --Contemporary Psychology
Book Synopsis Statistical Test Theory for the Behavioral Sciences by : Dato N. M. de Gruijter
Download or read book Statistical Test Theory for the Behavioral Sciences written by Dato N. M. de Gruijter and published by CRC Press. This book was released on 2007-08-31 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the development of the first intelligence test in the early 20th century, educational and psychological tests have become important measurement techniques to quantify human behavior. Focusing on this ubiquitous yet fruitful area of research, Statistical Test Theory for the Behavioral Sciences provides both a broad overview and a critical survey of assorted testing theories and models used in psychology, education, and other behavioral science fields. Following a logical progression from basic concepts to more advanced topics, the book first explains classical test theory, covering true score, measurement error, and reliability. It then presents generalizability theory, which provides a framework to deal with various aspects of test scores. In addition, the authors discuss the concept of validity in testing, offering a strategy for evidence-based validity. In the two chapters devoted to item response theory (IRT), the book explores item response models, such as the Rasch model, and applications, including computerized adaptive testing (CAT). The last chapter looks at some methods used to equate tests. Equipped with the essential material found in this book, advanced undergraduate and graduate students in the behavioral sciences as well as researchers involved in measurement and testing will gain valuable insight into the research methodologies and statistical data analyses of behavioral testing.
Book Synopsis Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences by : Brian S. Everitt
Download or read book Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences written by Brian S. Everitt and published by CRC Press. This book was released on 2009-09-28 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences shows students how to apply statistical methods to behavioral science data in a sensible manner. Assuming some familiarity with introductory statistics, the book analyzes a host of real-world data to provide useful answers to real-life issues.The author begins by exploring
Book Synopsis Statistical Power Analysis for the Social and Behavioral Sciences by : Xiaofeng Steven Liu
Download or read book Statistical Power Analysis for the Social and Behavioral Sciences written by Xiaofeng Steven Liu and published by Routledge. This book was released on 2013-11-07 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to demonstrate the application of power analysis to the newer more advanced statistical techniques that are increasingly used in the social and behavioral sciences. Both basic and advanced designs are covered. Readers are shown how to apply power analysis to techniques such as hierarchical linear modeling, meta-analysis, and structural equation modeling. Each chapter opens with a review of the statistical procedure and then proceeds to derive the power functions. This is followed by examples that demonstrate how to produce power tables and charts. The book clearly shows how to calculate power by providing open code for every design and procedure in R, SAS, and SPSS. Readers can verify the power computation using the computer programs on the book's website. There is a growing requirement to include power analysis to justify sample sizes in grant proposals. Most chapters are self-standing and can be read in any order without much disruption.This book will help readers do just that. Sample computer code in R, SPSS, and SAS at www.routledge.com/9781848729810 are written to tabulate power values and produce power curves that can be included in a grant proposal. Organized according to various techniques, chapters 1 – 3 introduce the basics of statistical power and sample size issues including the historical origin, hypothesis testing, and the use of statistical power in t tests and confidence intervals. Chapters 4 - 6 cover common statistical procedures -- analysis of variance, linear regression (both simple regression and multiple regression), correlation, analysis of covariance, and multivariate analysis. Chapters 7 - 11 review the new statistical procedures -- multi-level models, meta-analysis, structural equation models, and longitudinal studies. The appendixes contain a tutorial about R and show the statistical theory of power analysis. Intended as a supplement for graduate courses on quantitative methods, multivariate statistics, hierarchical linear modeling (HLM) and/or multilevel modeling and SEM taught in psychology, education, human development, nursing, and social and life sciences, this is the first text on statistical power for advanced procedures. Researchers and practitioners in these fields also appreciate the book‘s unique coverage of the use of statistical power analysis to determine sample size in planning a study. A prerequisite of basic through multivariate statistics is assumed.
Book Synopsis Statistical Power Analysis for the Behavioral Sciences by : Jacob Cohen
Download or read book Statistical Power Analysis for the Behavioral Sciences written by Jacob Cohen and published by Routledge. This book was released on 2013-05-13 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.
Book Synopsis Ordinal Data Modeling by : Valen E. Johnson
Download or read book Ordinal Data Modeling written by Valen E. Johnson and published by Springer Science & Business Media. This book was released on 2006-04-06 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ordinal Data Modeling is a comprehensive treatment of ordinal data models from both likelihood and Bayesian perspectives. A unique feature of this text is its emphasis on applications. All models developed in the book are motivated by real datasets, and considerable attention is devoted to the description of diagnostic plots and residual analyses. Software and datasets used for all analyses described in the text are available on websites listed in the preface.
Download or read book Marginal Models written by Wicher Bergsma and published by Springer Science & Business Media. This book was released on 2009-04-03 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Marginal Models for Dependent, Clustered, and Longitudinal Categorical Data provides a comprehensive overview of the basic principles of marginal modeling and offers a wide range of possible applications. Marginal models are often the best choice for answering important research questions when dependent observations are involved, as the many real world examples in this book show. In the social, behavioral, educational, economic, and biomedical sciences, data are often collected in ways that introduce dependencies in the observations to be compared. For example, the same respondents are interviewed at several occasions, several members of networks or groups are interviewed within the same survey, or, within families, both children and parents are investigated. Statistical methods that take the dependencies in the data into account must then be used, e.g., when observations at time one and time two are compared in longitudinal studies. At present, researchers almost automatically turn to multi-level models or to GEE estimation to deal with these dependencies. Despite the enormous potential and applicability of these recent developments, they require restrictive assumptions on the nature of the dependencies in the data. The marginal models of this book provide another way of dealing with these dependencies, without the need for such assumptions, and can be used to answer research questions directly at the intended marginal level. The maximum likelihood method, with its attractive statistical properties, is used for fitting the models. This book has mainly been written with applied researchers in mind. It includes many real world examples, explains the types of research questions for which marginal modeling is useful, and provides a detailed description of how to apply marginal models for a great diversity of research questions. All these examples are presented on the book's website (www.cmm.st), along with user friendly programs.
Book Synopsis Statistics for the Social and Behavioral Sciences by : David A. Kenny
Download or read book Statistics for the Social and Behavioral Sciences written by David A. Kenny and published by . This book was released on 1987 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advances in Social Network Analysis by : Stanley Wasserman
Download or read book Advances in Social Network Analysis written by Stanley Wasserman and published by SAGE Publications. This book was released on 1994-07-27 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social network analysis, a method for analyzing relationships between social entities, has expanded over the last decade as new research has been done in this area. How can these new developments be applied effectively in the behavioral and social sciences disciplines? In Advances in Social Network Analysis, a team of leading methodologists in network analysis addresses this issue. They explore such topics as ways to specify the network contents to be studied, how to select the method for representing network structures, how social network analysis has been used to study interorganizational relations via the resource dependence model, how to use a contact matrix for studying the spread of disease in epidemiology, and how cohesion and structural equivalence network theories relate to studying social influence. It also offers statistical models for social support networks. Advances in Social Network Analysis is useful for researchers involved in general research methods and qualitative methods, and who are interested in psychology and sociology.
Book Synopsis Fundamental Statistics for the Social and Behavioral Sciences by : Howard T. Tokunaga
Download or read book Fundamental Statistics for the Social and Behavioral Sciences written by Howard T. Tokunaga and published by SAGE Publications. This book was released on 2018-09-12 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamental Statistics for the Social and Behavioral Sciences, Second Edition, places statistics within the research process, illustrating how they are used to answer questions and test ideas. Students learn not only how to calculate statistics, but also how to interpret and communicate the results of statistical analyses in light of a study’s research hypothesis. Featuring accessible writing and well-integrated research examples, the book gives students a greater understanding of how research studies are conceived, conducted, and communicated. The Second Edition includes a new chapter on regression; covers how collected data can be organized, presented and summarized; the process of conducting statistical analyses to test research questions, hypotheses, and issues/controversies; and examines statistical procedures used in research situations that vary in the number of independent variables in the study. Every chapter includes learning checks, such as review questions and summary boxes, to reinforce the content students just learned, and exercises at the end of every chapter help assess their knowledge. Also new to the Second Edition -- animated video tutorials!
Book Synopsis Multivariate and Mixture Distribution Rasch Models by : Matthias Davier
Download or read book Multivariate and Mixture Distribution Rasch Models written by Matthias Davier and published by Springer Science & Business Media. This book was released on 2007-12-15 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines extensions of the Rasch model, one of the most researched and applied models in educational research and social science. This collection contains 22 chapters by some of the most renowned international experts in the field. They cover topics ranging from general model extensions to applications in fields as diverse as cognition, personality, organizational and sports psychology, and health sciences and education.
Book Synopsis Study Guide to Accompany Integrative Statistics for the Social and Behavioral Sciences by : Renee R. Ha
Download or read book Study Guide to Accompany Integrative Statistics for the Social and Behavioral Sciences written by Renee R. Ha and published by SAGE Publications. This book was released on 2011-06-28 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Student Study Guide to accompany Renee Ha and James Ha's 'Integrative Statistics for the Social and Behavioral Sciences' includes notes to the student, and multiple choice and short answer questions. Exercises are also included for students to test and apply their knowledge. Answers to all questions are also included. This Student Study Guide is also available in a bundle with the textbook at a discounted price. Bundle ISBN: 9781452205304.
Book Synopsis Handbook of Statistical Modeling for the Social and Behavioral Sciences by : G. Arminger
Download or read book Handbook of Statistical Modeling for the Social and Behavioral Sciences written by G. Arminger and published by Springer Science & Business Media. This book was released on 1995 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contributors thoroughly survey the most important statistical models used in empirical reserch in the social and behavioral sciences. Following a common format, each chapter introduces a model, illustrates the types of problems and data for which the model is best used, provides numerous examples that draw upon familiar models or procedures, and includes material on software that can be used to estimate the models studied. This handbook will aid researchers, methodologists, graduate students, and statisticians to understand and resolve common modeling problems.
Author :Wim J. van der Linden Publisher :Springer Science & Business Media ISBN 13 :0387290540 Total Pages :421 pages Book Rating :4.3/5 (872 download)
Book Synopsis Linear Models for Optimal Test Design by : Wim J. van der Linden
Download or read book Linear Models for Optimal Test Design written by Wim J. van der Linden and published by Springer Science & Business Media. This book was released on 2006-01-01 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wim van der Linden was just given a lifetime achievement award by the National Council on Measurement in Education. There is no one more prominent in the area of educational testing. There are hundreds of computer-based credentialing exams in areas such as accounting, real estate, nursing, and securities, as well as the well-known admissions exams for college, graduate school, medical school, and law school - there is great need on the theory of testing. This book presents the statistical theory and practice behind constructing good tests e.g., how is the first test item selected, how are the next items selected, and when do you have enough items.
