Applied Multivariate Statistics for the Social Sciences
Analyses with SAS and IBM's SPSS, Sixth Edition
6th Edition
Published on 7. December 2015
814 pages
978-1-317-80591-5 (ISBN)
Description
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.
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.
Reviews / Votes
The new edition maintains the tradition of the great Stevens book (with clear examples using both SAS/SPSS) while incorporating important new information. I also appreciate that this new edition gives more attention to the APA-style write-ups. I look forward to using the 6th edition of this text in my class.--Chris Oshima, Professor, Georgia State University
This new edition of Applied Multivariate Statistics for the Social Sciences is even more comprehensive; covering major advanced topics in the social sciences combined with excellent computer-based examples, in-depth discussions, and example write-ups. Yet, it is written in an accessible way that students will find useful and comprehensible.
--Namok Choi, Professor, University of Louisville The new edition maintains the tradition of the great Stevens book (with clear examples using both SAS/SPSS) while incorporating important new information. I also appreciate that this new edition gives more attention to the APA-style write-ups. I look forward to using the 6th edition of this text in my class. -Chris Oshima, Georgia State University, USA
This new edition of Applied Multivariate Statistics for the Social Sciences is even more comprehensive; covering major advanced topics in the social sciences combined with excellent computer-based examples, in-depth discussions, and example write-ups. Yet, it is written in an accessible way that students will find useful and comprehensible. -Namok Choi, University of Louisville, USA
While Stevens has always been my "go to" book for multivariate statistics, the revised 6th Edition by Pituch and Stevens improves significantly on the previous version with key chapter revisions and additions, as well as new analysis summaries and results write-ups. -Philip Schatz, Saint Joseph's University, USA
The revised 6th edition by Pituch and Stevens is a very valuable and well-written text that provides students with all they need to understand and apply multivariate data analysis. The authors did a great job in revising the chapters, and the new coverage of binary logistic regression, multivariate multilevel modeling, and missing data analysis are a "must" for both applied researchers and graduate students. -Karin Schermelleh-Engel, Goethe University, Germany
More details
Edition
6th edition
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
352 Tables, black and white; 65 Halftones, black and white
File size
7,28 MB
ISBN-13
978-1-317-80591-5 (9781317805915)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Keenan A. Pituch | James P. Stevens
Applied Multivariate Statistics for the Social Sciences
Analyses with SAS and IBM's SPSS, Sixth Edition
Book
11/2015
6th Edition
Routledge
€332.30
Shipment within 15-20 days
Keenan A. Pituch | James P. Stevens
Applied Multivariate Statistics for the Social Sciences
Analyses with SAS and IBM's SPSS, Sixth Edition
Book
11/2015
6th Edition
Routledge
€171.50
Shipment within 15-20 days
Persons
Keenan Pituch is Associate Professor in the Quantitative Methods Area of the Department of Educational Psychology at the University of Texas at Austin.
James P Stevens is Professor Emeritus at University of Cincinatti.
James P Stevens is Professor Emeritus at University of Cincinatti.
Content
1. Introduction
2. Matrix Algebra
3. Multiple Regression for Prediction
4. Two-Group Multivariate Analysis of Variance
5. K-Group MANOVA: A Priori and Post-Hoc Procedures
6. Assumptions in MANOVA
7. Factorial ANOVA and MANOVA
8. Analysis of Covariance
9. Exploratory Factor Analysis
10. Discriminant Analysis
11. Binary Logistic Regression
12. Repeated-Measures Analysis
13. Hierarchical Linear Modeling
14. Multivariate Multilevel Modeling
15. Canonical Correlation
16. Structural Equation Modeling
Appendix A: Statistical Tables
Appendix B: Obtaining Nonorthogonal Contrasts in Repeated Measures Design
Answers to Half of the Text problems
2. Matrix Algebra
3. Multiple Regression for Prediction
4. Two-Group Multivariate Analysis of Variance
5. K-Group MANOVA: A Priori and Post-Hoc Procedures
6. Assumptions in MANOVA
7. Factorial ANOVA and MANOVA
8. Analysis of Covariance
9. Exploratory Factor Analysis
10. Discriminant Analysis
11. Binary Logistic Regression
12. Repeated-Measures Analysis
13. Hierarchical Linear Modeling
14. Multivariate Multilevel Modeling
15. Canonical Correlation
16. Structural Equation Modeling
Appendix A: Statistical Tables
Appendix B: Obtaining Nonorthogonal Contrasts in Repeated Measures Design
Answers to Half of the Text problems
