Download or read book Research Issues Underlying Multivariate Methods written by William F. Massy and published by Marketing Classics Press. This book was released on 2011-06-30 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Essence of Multivariate Thinking written by Lisa L. Harlow and published by Routledge. This book was released on 2014-02-18 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: By focusing on underlying themes, this book helps readers better understand the connections between multivariate methods. For each method the author highlights: the similarities and differences between the methods, when they are used and the questions they address, the key assumptions and equations, and how to interpret the results. The concepts take center stage while formulas are kept to a minimum. Examples using the same data set give readers continuity so they can more easily apply the concepts. Each method is also accompanied by a worked out example, SPSS and SAS input, and an example of how to write up the results. EQS code is used for the book’s SEM applications. This extensively revised edition features: New SEM chapters including an introduction (ch.10), path analysis (ch.11), confirmatory factor analysis (ch.12), and latent variable modeling (ch.13) the last three with an EQS application. A new chapter on multilevel modeling (ch. 8) that is now used more frequently in the social sciences. More emphasis on significance tests, effect sizes, and confidence intervals to encourage readers to adopt a thorough approach to assessing the magnitude of their findings. A new data set that explores the work environment. More discussion about the basic assumptions and equations for each method for a more accessible approach. New examples that help clarify the distinctions between methods. A new website at https://sites.google.com/site/multivariatesecondedition/ that features the datasets for all of the examples in the book for use in both SPSS and SAS and in EQS for the SEM chapters. The first two chapters review the core themes that run through most multivariate methods. The author shows how understanding multivariate methods is much more achievable when we notice the themes that underlie these statistical techniques. This multiple level approach also provides greater reliability and validity in our research. After providing insight into the core themes, the author illustrates them as they apply to the most popular multivariate methods used in the social, and behavioral sciences. First, two intermediate methods are explored – multiple regression and analysis of covariance. Next the multivariate grouping variable methods of multivariate analysis of variance, discriminant function analysis, and logistic regression are explored. Next the themes are applied to multivariate modeling methods including multilevel modeling, path analysis, confirmatory factor analysis, and latent variable models that include exploratory structural methods of principal component and factor analysis. The book concludes with a summary of the common themes and how they pertain to each method discussed in this book. Intended for advanced undergraduate and/or graduate courses in multivariate statistics taught in psychology, education, human development, business, nursing, and other social and life sciences, researchers also appreciate this book‘s applied approach. Knowledge of basic statistics, research methods, basic algebra, and finite mathematics is recommended.
Download or read book Multivariate Methods for Market and Survey Research written by Jagdish N. Sheth and published by Marketing Classics Press. This book was released on 2011-06-30 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate Methods for Market and Survey Research is a graduate level book about different applications of methods in marketing research. It is a collection of papers from top names in the field of marketing and survey research. This collection discusses subjects from conjoint measurements and latent structure analysis to AID analysis, as well as further research areas related to these techniques.Dr. Jagdish (Jag) N. Sheth is the Charles H. Kellstadt Professor of Marketing in the Goizueta Business School at Emory University. Prior positions, include the University of Southern California; the University of Illinois; the faculty of Columbia University; and, the Massachusetts Institute of Technology. Dr. Sheth is well known for his scholarly contributions in consumer behavior, relationship marketing, competitive strategy and geopolitical analysis.
Download or read book Multivariate Data Analysis written by Joseph Hair and published by Pearson Higher Ed. This book was released on 2016-08-18 with total page 816 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For graduate and upper-level undergraduate marketing research courses. For over 30 years, Multivariate Data Analysis has provided readers with the information they need to understand and apply multivariate data analysis. Hair et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to readers how to understand and make use of the results of specific statistical techniques. In this Seventh Edition, the organization of the chapters has been greatly simplified. New chapters have been added on structural equations modeling, and all sections have been updated to reflect advances in technology, capability, and mathematical techniques.
Download or read book Multivariate Applications in Substance Use Research written by Jennifer S. Rose and published by Psychology Press. This book was released on 2000 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume introduces the latest advances in quantitative methods and illustrates ways to apply these methods to important questions in substance use research. The goal is to provide a forum for dialogue between methodologists developing innovative multivariate statistical methods and substance use researchers who have produced rich data sets. Reflecting current research trends, the book examines the use of longitudinal techniques to measure processes of change over time. Researchers faced with the task of studying the causes, course, treatment, and prevention of substance use and abuse will find this volume helpful for applying these techniques to make optimal use of their data. This innovative volume: introduces the use of latent curve methods for describing individual trajectories of adolescent substance use over time; explores methods for analyzing longitudinal data for individuals nested within groups, such as families, classrooms, and treatment groups; demonstrates how different patterns of missing data influence the interpretation of results; reports on some recent advances in longitudinal growth modeling; illustrates methods to assess mediation when there are multiple mediating pathways underlying an intervention effect; describes methods to identify moderating relations in structural equation models; demonstrates the use of structural equation models to evaluate a preventive intervention; applies epidemic modeling techniques to understand the spread of substance use in society; illustrates the use of latent transition analysis to model substance use as a series of stages; and applies logistic regression to prospectively predict smoking cessation.
Download or read book JMP for Basic Univariate and Multivariate Statistics written by Ann Lehman and published by SAS Institute. This book was released on 2013 with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Multivariate Analysis of Variance written by James H. Bray and published by SAGE. This book was released on 1985 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bray's monograph considers the multivariate form of analysis of variance (MANOVA). It is a technique which can be used in such different academic disciplines as psychology, sociology, biology, and education.
Download or read book Basic Statistics in Multivariate Analysis written by Karen A. Randolph and published by Oxford University Press. This book was released on 2013-01-24 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: The complexity of social problems necessitates that social work researchers understand and apply multivariate statistical methods in their investigations. In this pocket guide, the authors introduce readers to three of the more frequently used multivariate methods in social work research with an emphasis on basic statistics. The primary aim is to prepare entry-level doctoral students and early career social work researchers in the use of multivariate methods by providing an easy-to-understand presentation, building on the basic statistics that inform them. The pocket guide begins with a review of basic statistics, hypothesis testing with inferential statistics, and bivariate analytic methods. Subsequent sections describe bivariate and multiple linear regression analyses, one-way and two-way analysis of variance (ANOVA) and covariance (ANCOVA), and path analysis. In each chapter, the authors introduce the various basic statistical procedures by providing definitions, formulas, descriptions of the underlying logic and assumptions of each procedure, and examples of how they have been used in social work research literature, particularly with diverse populations. They also explain estimation procedures and how to interpret results. The multivariate chapters conclude with brief step-by-step instructions for conducting multiple regression analysis and one-way ANOVA in Statistical Package for the Social Sciences (SPSS), and path analysis in Amos, using data from the National Educational Longitudinal Study of 1988 (NELS: 88). As an additional supplement, the book offers a companion website that provides more detailed instructions, as well as data sets and worked examples.
Download or read book Making Sense of Multivariate Data Analysis written by John Spicer and published by SAGE. This book was released on 2005 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: A short introduction to the subject, this text is aimed at students & practitioners in the behavioural & social sciences. It offers a conceptual overview of the foundations of MDA & of a range of specific techniques including multiple regression, logistic regression & log-linear analysis.
Download or read book Analysis of Multivariate Social Science Data Second Edition written by David J. Bartholomew and published by Chapman and Hall/CRC. This book was released on 2008-06-04 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing on the authors’ varied experiences working and teaching in the field, Analysis of Multivariate Social Science Data, Second Editionenables a basic understanding of how to use key multivariate methods in the social sciences. With updates in every chapter, this edition expands its topics to include regression analysis, confirmatory factor analysis, structural equation models, and multilevel models. After emphasizing the summarization of data in the first several chapters, the authors focus on regression analysis. This chapter provides a link between the two halves of the book, signaling the move from descriptive to inferential methods and from interdependence to dependence. The remainder of the text deals with model-based methods that primarily make inferences about processes that generate data. Relying heavily on numerical examples, the authors provide insight into the purpose and working of the methods as well as the interpretation of data. Many of the same examples are used throughout to illustrate connections between the methods. In most chapters, the authors present suggestions for further work that go beyond conventional exercises, encouraging readers to explore new ground in social science research. Requiring minimal mathematical and statistical knowledge, this book shows how various multivariate methods reveal different aspects of data and thus help answer substantive research questions.
Download or read book Methods of Multivariate Analysis written by Alvin C. Rencher and published by John Wiley & Sons. This book was released on 2003-04-14 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Methods of Multivariate Analysis was among those chosen. When measuring several variables on a complex experimental unit, it is often necessary to analyze the variables simultaneously, rather than isolate them and consider them individually. Multivariate analysis enables researchers to explore the joint performance of such variables and to determine the effect of each variable in the presence of the others. The Second Edition of Alvin Rencher's Methods of Multivariate Analysis provides students of all statistical backgrounds with both the fundamental and more sophisticated skills necessary to master the discipline. To illustrate multivariate applications, the author provides examples and exercises based on fifty-nine real data sets from a wide variety of scientific fields. Rencher takes a "methods" approach to his subject, with an emphasis on how students and practitioners can employ multivariate analysis in real-life situations. The Second Edition contains revised and updated chapters from the critically acclaimed First Edition as well as brand-new chapters on: Cluster analysis Multidimensional scaling Correspondence analysis Biplots Each chapter contains exercises, with corresponding answers and hints in the appendix, providing students the opportunity to test and extend their understanding of the subject. Methods of Multivariate Analysis provides an authoritative reference for statistics students as well as for practicing scientists and clinicians.
Download or read book Multivariate Statistical Methods written by George A. Marcoulides and published by Psychology Press. This book was released on 2014-01-14 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate statistics refer to an assortment of statistical methods that have been developed to handle situations in which multiple variables or measures are involved. Any analysis of more than two variables or measures can loosely be considered a multivariate statistical analysis. An introductory text for students learning multivariate statistical methods for the first time, this book keeps mathematical details to a minimum while conveying the basic principles. One of the principal strategies used throughout the book--in addition to the presentation of actual data analyses--is pointing out the analogy between a common univariate statistical technique and the corresponding multivariate method. Many computer examples--drawing on SAS software --are used as demonstrations. Throughout the book, the computer is used as an adjunct to the presentation of a multivariate statistical method in an empirically oriented approach. Basically, the model adopted in this book is to first present the theory of a multivariate statistical method along with the basic mathematical computations necessary for the analysis of data. Subsequently, a real world problem is discussed and an example data set is provided for analysis. Throughout the presentation and discussion of a method, many references are made to the computer, output are explained, and exercises and examples with real data are included.
Download or read book Multivariable Analysis written by Mitchell H. Katz and published by Cambridge University Press. This book was released on 2006-02-09 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to perform and interpret multivariable analysis, using plain language rather than complex derivations.
Download or read book Multivariate Analysis of Variance MANOVA written by Harry R. Barker and published by . This book was released on 1984 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: Historical origins of MANOVA; Era of multivariate techniques; Sequential trends in application of multivariate techniques; Conceptual theory underlying MANOVA; Parallels between univariate ANOVA and multivariate MANOVA; Factor analysis and MANOVA; MANOVA tests of statistical significance; Differential sensitivity of test criteria related to distribution of trace; Assumptions underlying ANOVA and MANOVA; Decision strategies; Decision errors; ANOVA power analysis; MANOVA power analysis; Bonferroni t; Classic MANOVA procedure; Hummel-sligo procedure; Mixed strategy; Classic research designs; Two preliminary issues; Control checklist; Origin of all classic ANOVA designs; Extension of t test for independent groups; Extension of the t test for matched pairs (subject as his or her own control); Mixed designs; Applications of MANOVA to classic research designs; Preliminary considerations; Classic designs; Application of MANOVA to univariate designs that involve repeated measures; Distinction between MANOVA applied to univariate and multivariate repeated-measures designs; Univariate analysis of repeated measures; A univariate procedure for analyzing repeated-measures designs; Multivariate analysis of variance of repeated-measures designs; Checklist for the investigator conducting MANOVA research; Decision to conduct a study or experiment; Selection of dependent variables; Selection of a MANOVA test criterion; Statement of problem; Research design; Computer program test; Selection of MANOVA strategy; Hierarchy of hypotheses; Reporting multivariate outcomes; Hand-calculated example of one-way (simple randomized) MANOVA.
Download or read book Multivariate Methods in Epidemiology written by Theodore R. Holford and published by Oxford University Press. This book was released on 2002-05-30 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: The basis for much of medical public health practice comes from epidemiological research. This text describes current statistical tools that are used to analyze the association between possible risk factors and the actual risk of disease. Beginning with a broad conceptual framework on the disease process, it describes commonly used techniques for analyzing proportions and disease rates. These are then extended to model fitting, and the common threads of logic that bind the two analytic strategies together are revealed. Each chapter provides a descriptive rationale for the method, a worked example using data from a published study, and an exercise that allows the reader to practice the technique. Each chapter also includes an appendix that provides further details on the theoretical underpinnings of the method. Among the topics covered are Mantel-Haenszel methods, rates, survival analysis, logistic regression, and generalized linear models. Methods for incorporating aspects of study design, such as matching, into the analysis are discussed, and guidance is given for determining the power or the sample size requirements of a study. This text will give readers a foundation in applied statistics and the concepts of model fitting to develop skills in the analysis of epidemiological data.
Download or read book Research Methods in Psychology written by Glynis Marie Breakwell and published by SAGE. This book was released on 2006 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Third Edition of this bestselling text retains its status as one of the most accessible, practically useful and theoretically rigorous textbooks on the market today, and has been developed even further to help students get the most from their studies. The textbook is now oriented around three parts focusing on the major processed in conducting research-from formulating research questions, designing research activity, data gathering, and analysis. A rich diversity of methods is now covered, and the book offers extended coverage of qualitative methods-now fundamental in psychological methods courses.
Download or read book Advanced and Multivariate Statistical Methods written by Craig A. Mertler and published by Routledge. This book was released on 2005 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: - All the statistics traditionally covered in a second-level course are included. - Stresses the conceptual and practical aspects for students who do not need emphasis on the underlying mathematical theory. - Students learn not only the purpose of and how to compute the statistics using SPSS, they also learn the logic behind the techniques and how to test the underlying assumptions. - Students are shown how to interpret, present, and write up the results for each technique. - Exercises allow students to practice their newly acquired skills. The answer key will be provided with professors' copies. - If your students are overwhelmed by advanced statistics texts that are too technical and mathematical, you should examine this highly applied approach to multivariate statistics. Covers why, what, when and how. Ideal for nonmath majors. - The numerous screenshots and examples of output make it easy for students to follow the text. - Each statistical method is followed by an explanation of why a student might use that method, including a discussion of its purpose and sample research questions it can address. - The authors also show a sample study with an example of how to write up the results. Students see firsthand how to present their statistical findings. - Although SPSS is the program that is illustrated, students using any program will benefit greatly from the conceptual material.
