Applied Multivariate Statistics for the Social Sciences

Author: James Paul Stevens

Publisher: Taylor & Francis

ISBN: 0805859012

Category: Social Science

Page: 651

View: 4424

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This best-selling text is written for those who use, rather than develop statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than on proving results. Helpful narrative and numerous examples enhance understanding and a chapter on matrix algebra serves as a review. Annotated printouts from SPSS and SAS indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use these packages, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size by providing guidelines so that the results can be generalized. The book is noted for its extensive applied coverage of MANOVA, its emphasis on statistical power, and numerous exercises including answers to half. The new edition features: New chapters on Hierarchical Linear Modeling (Ch. 15) and Structural Equation Modeling (Ch. 16) New exercises that feature recent journal articles to demonstrate the actual use of multiple regression (Ch. 3), MANOVA (Ch. 5), and repeated measures (Ch. 13) A new appendix on the analysis of correlated observations (Ch. 6) Expanded discussions on obtaining non-orthogonal contrasts in repeated measures designs with SPSS and how to make the identification of cell ID easier in log linear analysis in 4 or 5 way designs Updated versions of SPSS (15.0) and SAS (8.0) are used throughout the text and introduced in chapter 1 A book website with data sets and more. Ideal for courses on multivariate statistics found in psychology, education, sociology, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial ANOVA and covariance. Working knowledge of matrix algebra is not assumed.

Cognitive Learning and Memory in Children

Progress in Cognitive Development Research

Author: M. Pressley,C.J. Brainerd

Publisher: Springer Science & Business Media

ISBN: 1461395445

Category: Psychology

Page: 250

View: 6338

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For some time now, the study of cognitive development has been far and away the most active discipline within developmental psychology. Although there would be much disagreement as to the exact proportion of papers published in developmental journals that could be considered cognitive, 50% seems like a conservative estimate. Hence, a series of scholarly books devoted to work in cognitive development is especially appropriate at this time. The Springer Series in Cognitive Development contains two basic types of books, namely, edited collections of original chapters by several authors, and original volumes written by one author or a small group of authors. The flagship for the Springer Series is a serial pUblication of the" advances" type, carrying the subtitle Progress in Cognitive Development Research. Each volume in the Progress sequence is strongly thematic, in that it is limited to some well-defined domain of cognitive-developmental research (e. g. , logical and mathematical development, development of learning). All Progress volumes will be edited collections. Editors of such collections, upon consultation with the Series Editor, may elect to have their books published either as contributions to the Progress sequence or as separate volumes. All books written by one author or a small group of authors are being published as separate volumes within the series. A fairly broad definition of cognitive development is being used in the selection of books for this series.

Basic Statistics in Multivariate Analysis

Author: Karen A. Randolph,Laura L. Myers

Publisher: Oxford University Press

ISBN: 0199764042

Category: Social Science

Page: 213

View: 9686

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This pocket guide introduces readers to linear regression analysis, analysis of variance and covariance, and path analysis with an emphasis on the basic statistics. It prepares doctoral students and early career social work researchers with limited statistics exposure in the use of multivariate methods by providing an easy-to-understand presentation.

Multivariate Analysis Techniques in Social Science Research

From Problem to Analysis

Author: J. J. A. Tacq,Professor Jacques Tacq

Publisher: SAGE

ISBN: 9781446237410

Category:

Page: 432

View: 5754

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Unlike most statistical texts, this book breathes real life into multivariate analysis. Starting with a range of actual research examples in the social sciences, it demonstrates how to make the most appropriate choice of technique. The examples are drawn from a broad spectrum of disciplines including: sociology, psychology, economics, political science and international comparative research.

The Reviewer’s Guide to Quantitative Methods in the Social Sciences

Author: Gregory R. Hancock,Ralph O. Mueller

Publisher: Routledge

ISBN: 1135172994

Category: Education

Page: 448

View: 4538

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The Reviewer’s Guide is designed for reviewers of research manuscripts and proposals in the social and behavioral sciences, and beyond. Its uniquely structured chapters address traditional and emerging quantitative methods of data analysis.

Research Methodology: A Guide for Researchers In Agricultural Science, Social Science and Other Related Fields

Author: Pradip Kumar Sahu

Publisher: Springer Science & Business Media

ISBN: 8132210204

Category: Technology & Engineering

Page: 432

View: 2240

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This book is the outcome of more than 20 years of experience of the author in teaching and research field. The wider scope and coverage of the book will help not only the students/ researchers/professionals in the field of agriculture and allied disciplines, but also the researchers and practitioners in other fields. Written in simple and lucid language, the book would appeal to all those who are meant to be benefitted out of it. All efforts have been made to present "RESEARCH", its meaning, intention and usefulness. The book reflects current methodological techniques used in interdisciplinary research, as illustrated with many relevant worked out examples. Designing of research programme, selection of variables, collection of data and their analysis to interpret the data are discussed extensively. Statistical tools are complemented with real-life examples, making the otherwise complicated subject like statistics seem simpler. Attempts have been made to demonstrate how a user can solve the problems using simple computer-oriented programme. Emphasis is placed not only on solving the problems in various fields but also on drawing inferences from the problems. The importance of instruments and computers in research processes and statistical analyses along with their misuse/incorrect use is also discussed to make the user aware about the correct use of specific technique. In all the chapters, theories are combined with examples, and steps are enumerated to follow the correct use of the available packages like MSEXCELL, SPSS, SPAR1, SAS etc. Utmost care has been taken to present varied range of research problems along with their solutions in agriculture and allied fields which would be of immense use to readers.

Applied Multivariate Statistics for the Social Sciences

Analyses with SAS and IBM’s SPSS, Sixth Edition

Author: Keenan A. Pituch,James P. Stevens

Publisher: Routledge

ISBN: 1317805917

Category: Psychology

Page: 814

View: 9003

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Now in its 6th edition, the authoritative textbook Applied Multivariate Statistics for the Social Sciences, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research studies. With the added expertise of co-author Keenan Pituch (University of Texas-Austin), this 6th edition retains many key features of the previous editions, including its breadth and depth of coverage, a review chapter on matrix algebra, applied coverage of MANOVA, and emphasis on statistical power. In this new edition, the authors continue to provide practical guidelines for checking the data, assessing assumptions, interpreting, and reporting the results to help students analyze data from their own research confidently and professionally. Features new to this edition include: NEW chapter on Logistic Regression (Ch. 11) that helps readers understand and use this very flexible and widely used procedure NEW chapter on Multivariate Multilevel Modeling (Ch. 14) that helps readers understand the benefits of this "newer" procedure and how it can be used in conventional and multilevel settings NEW Example Results Section write-ups that illustrate how results should be presented in research papers and journal articles NEW coverage of missing data (Ch. 1) to help students understand and address problems associated with incomplete data Completely re-written chapters on Exploratory Factor Analysis (Ch. 9), Hierarchical Linear Modeling (Ch. 13), and Structural Equation Modeling (Ch. 16) with increased focus on understanding models and interpreting results NEW analysis summaries, inclusion of more syntax explanations, and reduction in the number of SPSS/SAS dialogue boxes to guide students through data analysis in a more streamlined and direct approach Updated syntax to reflect newest versions of IBM SPSS (21) /SAS (9.3) A free online resources site at www.routledge.com/9780415836661 with data sets and syntax from the text, additional data sets, and instructor’s resources (including PowerPoint lecture slides for select chapters, a conversion guide for 5th edition adopters, and answers to exercises). Ideal for advanced graduate-level courses in education, psychology, and other social sciences in which multivariate statistics, advanced statistics, or quantitative techniques courses are taught, this book also appeals to practicing researchers as a valuable reference. Pre-requisites include a course on factorial ANOVA and covariance; however, a working knowledge of matrix algebra is not assumed.

JMP for Basic Univariate and Multivariate Statistics

Methods for Researchers and Social Scientists, Second Edition

Author: Ann Lehman,Norm O'Rourke,Larry Hatcher,Edward Stepanski

Publisher: SAS Institute

ISBN: 1612906036

Category: Computers

Page: 558

View: 501

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Learn how to manage JMP data and perform the statistical analyses most commonly used in research in the social sciences and other fields with JMP for Basic Univariate and Multivariate Statistics: Methods for Researchers and Social Scientists, Second Edition. Updated for JMP 10 and including new features on the statistical platforms, this book offers clearly written instructions to guide you through the basic concepts of research and data analysis, enabling you to easily perform statistical analyses and solve problems in real-world research. Step by step, you'll discover how to obtain descriptive and inferential statistics, summarize results clearly in a way that is suitable for publication, perform a wide range of JMP analyses, interpret the results, and more. Topics include screening data for errors selecting subsets computing the coefficient alpha reliability index (Cronbach's alpha) for a multiple-item scale performing bivariate analyses for all types of variables performing a one-way analysis of variance (ANOVA), multiple regression, and a one-way multivariate analysis of variance (MANOVA) Advanced topics include analyzing models with interactions and repeated measures. There is also comprehensive coverage of principle components with emphasis on graphical interpretation. This user-friendly book introduces researchers and students of the social sciences to JMP and to elementary statistical procedures, while the more advanced statistical procedures that are presented make it an invaluable reference guide for experienced researchers as well.

Neural Networks

An Introductory Guide for Social Scientists

Author: G David Garson

Publisher: SAGE

ISBN: 0761957308

Category: Social Science

Page: 194

View: 4851

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This book provides the first accessible introduction to neural network analysis as a methodological strategy for social scientists. The author details numerous studies and examples which illustrate the advantages of neural network analysis over other quantitative and modelling methods in widespread use. Methods are presented in an accessible style.

Using R With Multivariate Statistics

Author: Randall E. Schumacker

Publisher: SAGE Publications

ISBN: 1483377989

Category: Social Science

Page: 408

View: 9203

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Using R with Multivariate Statistics by Randall E. Schumacker is a quick guide to using R, free-access software available for Windows and Mac operating systems that allows users to customize statistical analysis. Designed to serve as a companion to a more comprehensive text on multivariate statistics, this book helps students and researchers in the social and behavioral sciences get up to speed with using R. It provides data analysis examples, R code, computer output, and explanation of results for every multivariate statistical application included. In addition, R code for some of the data set examples used in more comprehensive texts is included, so students can run examples in R and compare results to those obtained using SAS, SPSS, or STATA. A unique feature of the book is the photographs and biographies of famous persons in the field of multivariate statistics.

Multivariate Analysis for the Biobehavioral and Social Sciences

A Graphical Approach

Author: Bruce L. Brown,Suzanne B. Hendrix,Dawson W. Hedges,Timothy B. Smith

Publisher: John Wiley & Sons

ISBN: 1118131614

Category: Mathematics

Page: 496

View: 6744

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An insightful guide to understanding and visualizing multivariatestatistics using SAS®, STATA®, and SPSS® Multivariate Analysis for the Biobehavioral and Social Sciences:A Graphical Approach outlines the essential multivariate methodsfor understanding data in the social and biobehavioral sciences.Using real-world data and the latest software applications, thebook addresses the topic in a comprehensible and hands-on manner,making complex mathematical concepts accessible to readers. The authors promote the importance of clear, well-designedgraphics in the scientific process, with visual representationsaccompanying the presented classical multivariate statisticalmethods . The book begins with a preparatory review of univariatestatistical methods recast in matrix notation, followed by anaccessible introduction to matrix algebra. Subsequent chaptersexplore fundamental multivariate methods and related key concepts,including: Factor analysis and related methods Multivariate graphics Canonical correlation Hotelling's T-squared Multivariate analysis of variance (MANOVA) Multiple regression and the general linear model (GLM) Each topic is introduced with a research-publication case studythat demonstrates its real-world value. Next, the question "how doyou do that?" is addressed with a complete, yet simplified,demonstration of the mathematics and concepts of the method.Finally, the authors show how the analysis of the data is performedusing Stata®, SAS®, and SPSS®. The discussedapproaches are also applicable to a wide variety of modernextensions of multivariate methods as well as modern univariateregression methods. Chapters conclude with conceptual questionsabout the meaning of each method; computational questions that testthe reader's ability to carry out the procedures on simpledatasets; and data analysis questions for the use of the discussedsoftware packages. Multivariate Analysis for the Biobehavioral and Social Sciencesis an excellent book for behavioral, health, and social sciencecourses on multivariate statistics at the graduate level. The bookalso serves as a valuable reference for professionals andresearchers in the social, behavioral, and health sciences whowould like to learn more about multivariate analysis and itsrelevant applications.

Handbook of Applied Multivariate Statistics and Mathematical Modeling

Author: Howard E.A. Tinsley,Steven D. Brown

Publisher: Academic Press

ISBN: 9780080533568

Category: Mathematics

Page: 721

View: 6557

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Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many practicing researchers lack an adequate knowledge of these techniques, or did once know the techniques, but have not been able to keep abreast of new developments. The Handbook of Applied Multivariate Statistics and Mathematical Modeling explains the appropriate uses of multivariate procedures and mathematical modeling techniques, and prescribe practices that enable applied researchers to use these procedures effectively without needing to concern themselves with the mathematical basis. The Handbook emphasizes using models and statistics as tools. The objective of the book is to inform readers about which tool to use to accomplish which task. Each chapter begins with a discussion of what kinds of questions a particular technique can and cannot answer. As multivariate statistics and modeling techniques are useful across disciplines, these examples include issues of concern in biological and social sciences as well as the humanities.

Making Sense of Multivariate Data Analysis

An Intuitive Approach

Author: John Spicer

Publisher: SAGE

ISBN: 9781412904018

Category: Mathematics

Page: 233

View: 8651

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′This book is a helpful guide to reading and understanding multivariate data analysis results in social and psychological research′ _C. Y. Joanne Peng, Indiana University at Bloomington ′This book serves as a resource for readers who want to have an overall view of what encompasses multivariate analyses. The author has discussed some important issues rather philosophically (e.g., theory vs. data analysis). These points are valuable even for readers who have extensive training with multivariate analyses′ _Jenn-Yun Tein, Arizona State University

Applied Meta-analysis for Social Science Research

Author: Noel A. Card

Publisher: Guilford Press

ISBN: 1609184998

Category: Psychology

Page: 377

View: 3249

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Offering pragmatic guidance for planning and conducting a meta-analytic review, this book is written in an engaging, nontechnical style that makes it ideal for graduate course use or self-study. The author shows how to identify questions that can be answered using meta-analysis, retrieve both published and unpublished studies, create a coding manual, use traditional and unique effect size indices, and write a meta-analytic review. An ongoing example illustrates meta-analytic techniques. In addition to the fundamentals, the book discusses more advanced topics, such as artifact correction, random- and mixed-effects models, structural equation representations, and multivariate procedures. User-friendly features include annotated equations; discussions of alternative approaches; and "Practical Matters" sections that give advice on topics not often discussed in other books, such as linking meta-analytic results with theory and the utility of meta-analysis software programs.

The Psychology Research Handbook

A Guide for Graduate Students and Research Assistants

Author: Frederick T. L. Leong,James T. Austin

Publisher: SAGE

ISBN: 0761930221

Category: Psychology

Page: 516

View: 3839

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A comprehensive, easy-to-understand guide to the entire research process, this book quickly and efficiently equips advanced students and research assistants to conduct a full-scale investigation. The book is organized around the idea of a 'research script' that is, it follows the standard mode of research planning and design, data collection and analysis, and results writing. The volume contains 35 chapters, some co-authored by advanced graduate students who give their fellow students a touch of the 'real world' adding to the clarity and practicality of many chapters.

Quantitative Data Analysis with Minitab

A Guide for Social Scientists

Author: Alan Bryman,Professor of Organizational and Social Research Alan Bryman,Duncan Cramer

Publisher: Routledge

ISBN: 1134805748

Category: Psychology

Page: 302

View: 4308

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Quantitative data analysis is now a compulsory component of most degree courses in the social sciences and students are increasingly reliant on computers for the analysis of data. Quantitative Data Analysis with Minitab explains statistical tests for Minitab users using the same formulae free, non technical approach, as the very successful SPPS version. Students will learn a wide range of quantitative data analysis techniques and become familiar with how these techniques can be implemented through the latest version of Minitab. Techniques covered include univariate analysis (with frequency table, dispersion and histograms), bivariate (with contingency tables correlation, analysis of varience and non-parametric tests) and multivariate analysis (with multiple regression, path analysis, covarience and factor analysis). In addition the book covers issues such as sampling, statistical significance, conceptualisation and measurement and the selection of appropriate tests. Each chapter concludes with a set of exercises. Social science students will welcome this integrated, non mathematical introduction to quantitative data anlysis and the minitab package.

Using LISREL for Structural Equation Modeling

A Researcher's Guide

Author: E. Kevin Kelloway

Publisher: SAGE

ISBN: 9780761906261

Category: Mathematics

Page: 147

View: 877

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This highly readable introduction to structural equation modeling is designed for researchers and graduate students in the social sciences who want to use structural equation modeling techniques to answer substantive research questions. An overview of structural equation modeling includes the theory and logic of structural equation models, assessing the "fit" of structural equation models to the data, and their SEMs implementation in the LISREL environment.