Statistical Models For The Social And Behavioral Sciences

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Handbook of Statistical Modeling for the Social and Behavioral Sciences

Author : G. Arminger
Publisher : Springer Science & Business Media
ISBN 13 : 1489912924
Total Pages : 603 pages
Book Rating : 4.4/5 (899 download)

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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.

Statistical Models for the Social and Behavioral Sciences

Author : James H. Dwyer
Publisher : Oxford University Press, USA
ISBN 13 :
Total Pages : 506 pages
Book Rating : 4.F/5 ( download)

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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:

Statistical Methods for the Social and Behavioural Sciences

Author : David B. Flora
Publisher : SAGE
ISBN 13 : 1526421925
Total Pages : 769 pages
Book Rating : 4.5/5 (264 download)

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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.

Statistical Power Analysis for the Social and Behavioral Sciences

Author : Xiaofeng Steven Liu
Publisher : Routledge
ISBN 13 : 1136464182
Total Pages : 285 pages
Book Rating : 4.1/5 (364 download)

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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.

Statistics for the Social and Behavioral Sciences

Author : David A. Kenny
Publisher :
ISBN 13 : 9780316489157
Total Pages : 407 pages
Book Rating : 4.4/5 (891 download)

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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:

Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences

Author : Brian S. Everitt
Publisher : CRC Press
ISBN 13 : 1439807701
Total Pages : 324 pages
Book Rating : 4.4/5 (398 download)

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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

Handbook of Statistical Modeling for the Social and Behavioral Sciences

Author : G. Arminger
Publisher : Springer Science & Business Media
ISBN 13 : 9780306448058
Total Pages : 592 pages
Book Rating : 4.4/5 (48 download)

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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 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.

Marginal Models

Author : Wicher Bergsma
Publisher : Springer Science & Business Media
ISBN 13 : 0387096108
Total Pages : 274 pages
Book Rating : 4.3/5 (87 download)

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Book Synopsis Marginal Models by : Wicher Bergsma

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.

Ordinal Data Modeling

Author : Valen E. Johnson
Publisher : Springer Science & Business Media
ISBN 13 : 0387227024
Total Pages : 258 pages
Book Rating : 4.3/5 (872 download)

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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.

Fundamental Statistics for the Social and Behavioral Sciences

Author : Howard T. Tokunaga
Publisher : SAGE Publications
ISBN 13 : 1506377467
Total Pages : 740 pages
Book Rating : 4.5/5 (63 download)

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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!

Statistical Power Analysis for the Behavioral Sciences

Author : Jacob Cohen
Publisher : Routledge
ISBN 13 : 1134742770
Total Pages : 625 pages
Book Rating : 4.1/5 (347 download)

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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.

Study Guide to Accompany Integrative Statistics for the Social and Behavioral Sciences

Author : Renee R. Ha
Publisher : SAGE Publications
ISBN 13 : 1483341844
Total Pages : 97 pages
Book Rating : 4.4/5 (833 download)

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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.

Advances in Social Network Analysis

Author : Stanley Wasserman
Publisher : SAGE Publications
ISBN 13 : 1452253919
Total Pages : 320 pages
Book Rating : 4.4/5 (522 download)

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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.

Advanced Statistics for the Behavioral Sciences

Author : Jonathon D. Brown
Publisher : Springer
ISBN 13 : 3319935496
Total Pages : 526 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Advanced Statistics for the Behavioral Sciences by : Jonathon D. Brown

Download or read book Advanced Statistics for the Behavioral Sciences written by Jonathon D. Brown and published by Springer. This book was released on 2019-04-30 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demonstrates the importance of computer-generated statistical analyses in behavioral science research, particularly those using the R software environment. Statistical methods are being increasingly developed and refined by computer scientists, with expertise in writing efficient and elegant computer code. Unfortunately, many researchers lack this programming background, leaving them to accept on faith the black-box output that emerges from the sophisticated statistical models they frequently use. Building on the author’s previous volume, Linear Models in Matrix Form, this text bridges the gap between computer science and research application, providing easy-to-follow computer code for many statistical analyses using the R software environment. The text opens with a foundational section on linear algebra, then covers a variety of advanced topics, including robust regression, model selection based on bias and efficiency, nonlinear models and optimization routines, generalized linear models, and survival and time-series analysis. Each section concludes with a presentation of the computer code used to illuminate the analysis, as well as pointers to packages in R that can be used for similar analyses and nonstandard cases. The accessible code and breadth of topics make this book an ideal tool for graduate students or researchers in the behavioral sciences who are interested in performing advanced statistical analyses without having a sophisticated background in computer science and mathematics.

Statistical Models for the Social and Behavioral Sciences

Author : William H. Crown
Publisher : Praeger
ISBN 13 :
Total Pages : 208 pages
Book Rating : 4.3/5 (91 download)

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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.

Statistical Science in the Courtroom

Author : Joseph L. Gastwirth
Publisher : Springer Science & Business Media
ISBN 13 : 1461212162
Total Pages : 454 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Statistical Science in the Courtroom by : Joseph L. Gastwirth

Download or read book Statistical Science in the Courtroom written by Joseph L. Gastwirth and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Expert testimony relying on scientific and other specialized evidence has come under increased scrutiny by the legal system. A trilogy of recent U.S. Supreme Court cases has assigned judges the task of assessing the relevance and reliability of proposed expert testimony. In conjunction with the Federal judiciary, the American Association for the Advancement of Science has initiated a project to provide judges indicating a need with their own expert. This concern with the proper interpretation of scientific evidence, especially that of a probabilistic nature, has also occurred in England, Australia and in several European countries. Statistical Science in the Courtroom is a collection of articles written by statisticians and legal scholars who have been concerned with problems arising in the use of statistical evidence. A number of articles describe DNA evidence and the difficulties of properly calculating the probability that a random individual's profile would "match" that of the evidence as well as the proper way to intrepret the result. In addition to the technical issues, several authors tell about their experiences in court. A few have become disenchanted with their involvement and describe the events that led them to devote less time to this application. Other articles describe the role of statistical evidence in cases concerning discrimination against minorities, product liability, environmental regulation, the appropriateness and fairness of sentences and how being involved in legal statistics has raised interesting statistical problems requiring further research.

Generalized Linear Models for Categorical and Continuous Limited Dependent Variables

Author : Michael Smithson
Publisher : CRC Press
ISBN 13 : 1466551739
Total Pages : 310 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Generalized Linear Models for Categorical and Continuous Limited Dependent Variables by : Michael Smithson

Download or read book Generalized Linear Models for Categorical and Continuous Limited Dependent Variables written by Michael Smithson and published by CRC Press. This book was released on 2013-09-05 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generalized Linear Models for Categorical and Continuous Limited Dependent Variables is designed for graduate students and researchers in the behavioral, social, health, and medical sciences. It incorporates examples of truncated counts, censored continuous variables, and doubly bounded continuous variables, such as percentages. The book provides broad, but unified, coverage, and the authors integrate the concepts and ideas shared across models and types of data, especially regarding conceptual links between discrete and continuous limited dependent variables. The authors argue that these dependent variables are, if anything, more common throughout the human sciences than the kind that suit linear regression. They cover special cases or extensions of models, estimation methods, model diagnostics, and, of course, software. They also discuss bounded continuous variables, boundary-inflated models, and methods for modeling heteroscedasticity. Wherever possible, the authors have illustrated concepts, models, and techniques with real or realistic datasets and demonstrations in R and Stata, and each chapter includes several exercises at the end. The illustrations and exercises help readers build conceptual understanding and fluency in using these techniques. At several points the authors bring together material that has been previously scattered across the literature in journal articles, software package documentation files, and blogs. These features help students learn to choose the appropriate models for their purpose.