IBM SPSS for Intermediate Statistics
Use and Interpretation, Fifth Edition
Routledge – 2015 – 376 pages
Designed to help readers analyze and interpret research data using IBM SPSS, this user-friendly book shows readers how to choose the appropriate statistic based on the design; perform intermediate statistics, including multivariate statistics; interpret output; and write about the results. The book reviews research designs and how to assess the accuracy and reliability of data; how to determine whether data meet the assumptions of statistical tests; how to calculate and interpret effect sizes for intermediate statistics, including odds ratios for logistic and discriminant analyses; how to compute and interpret post-hoc power; and an overview of basic statistics for those who need a review. Unique chapters on multilevel linear modeling; multivariate analysis of variance (MANOVA); assessing reliability of data; multiple imputation; mediation, moderation, and canonical correlation; and factor analysis are provided. SPSS syntax with output is included for those who prefer this format.
The new edition features:
• IBM SPSS version 22; although the book can be used with most older and newer versions
• New discusiion of intraclass correlations (Ch. 3)
• Expanded discussion of effect sizes that includes confidence intervals of effect sizes (ch.5)
• New information on part and partial correlations and how they are interpreted and a new discussion on backward elimination, another useful multiple regression method (Ch. 6)
• New chapter on how use a variable as a mediator or a moderator (ch. 7)
• Revised chapter on multilevel and hierarchical linear modeling (ch. 12)
• A new chapter (ch. 13) on multiple imputation that demonstrates how to deal with missing data
• Updated web resources for instructors including PowerPoint slides, answers to interpretation questions, extra SPSS problems and for students, data sets, and chapter outlines and study guides.
IBM SPSS for Intermediate Statistics, Fifth Edition provides helpful teaching tools:
• all of the key SPSS windows needed to perform the analyses
• outputs with call-out boxes to highlight key points
• interpretation sections and questions to help students better understand and interpret the output
• extra problems with realistic data sets for practice using intermediate statistics
• Appendices on how to get started with SPSS, write research questions, and basic statistics.
An ideal supplement for courses in either intermediate/advanced statistics or research methods taught in departments of psychology, education, and other social, behavioral, and health sciences. This book is also appreciated by researchers in these areas looking for a handy reference for SPSS
1. Introduction 2. Data Coding and Exploratory Analysis (EDA) 3. Imputation of Missing Data 4. Several Measures of Reliability 5. Exploratory Factor Analysis and Principal Components Analysis 6. Selecting and Interpreting Inferential Statistics 7. Multiple Regression 8. Mediation, Moderation, and Canonical Correlation 9. Logistic Regression and Discriminant Analysis 10. Factorial ANOVA and ANCOVA 11. Repeated-Measures and Mixed ANOVAs 12. Multivariate Analysis of Variance (MANOVA) 13. Multilevel Linear Modeling/Hierarchical Linear Modeling Appendix A. Getting Started With SPSS and Other Useful Procedures D. Quick, M. Myers Appendix B. Review of Basic Statistics J.M. Cumming, A. Weinberg Appendix C. Answers to Odd Interpretation Questions
Nancy Leech is an Associate Professor at the University of Colorado Denver. She received her Ph.D. in education with an emphasis on research and statistics from Colorado State University in 2002. Dr. Leech is currently teaching graduate level courses in research, statistics, and measurement. Her area of research is promoting new developments and better understandings in applied qualitative, quantitative, and mixed methodologies.
Karen C. Barrett is Professor of Human Development and Family Studies with a joint appointment in Psychology at Colorado State University. She received her Ph.D. from the University of Denver. She is Assistant Department head of HDFS and teaches graduate level research methods and statistics courses. Her research regards emotion regulation and its influence on development; social emotions such as guilt and shame; and family and cultural influences on emotions.
George A. Morgan is Emeritus Professor of Education and Human Development at Colorado State University. He received his Ph.D. in child development and psychology from Cornell University. In addition to writing textbooks on SPSS and research methods, he has advised many PhD students in education and related fields. Over the past 35 years, he has conducted a program of research on children’s motivation to master challenging tasks.