ANOVA (Analysis Of Variance) is one of the most fundamental and ubiquitous univariate methodologies employed by psychologists and other behavioural scientists. Analysis of Variance Designs presents the foundations of this experimental design, including assumptions, statistical significance, strength of effect, and the partitioning of the variance. Exploring the effects of one or more independent variables on a single dependent variable as well as two-way and three-way mixed designs, this textbook offers an overview of traditionally advanced topics for advanced undergraduates and graduate students in the behavioural and social sciences. Separate chapters are devoted to multiple comparisons (post hoc and planned/weighted), ANCOVA, and advanced topics. Each of the design chapters contains conceptual discussions, hand calculations, and procedures for the omnibus and simple effects analyses in both SPSS and the new 'click and shoot' SAS Enterprise Guide interface.
- Appeals to undergraduates taking a second statistics course and master and doctoral students in applied subjects
- Each chapter contains applications sections showing how methods discussed in text can be implemented in the software package SPSS
- Presents traditionally advanced material such as ANOVA in an accessible way for undergraduates
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Product details
- Date Published: November 2008
- format: Hardback
- isbn: 9780521874816
- length: 594 pages
- dimensions: 260 x 183 x 37 mm
- weight: 1.19kg
- contains: 38 tables 36 exercises
- availability: Available
Table of Contents
1. ANOVA and research design
2. Measurement, central tendency, and variability
3. Elements of ANOVA
4. The statistical significance and effect of strength
5. Analysis of variance assumptions
6. One-way between subjects design
7. Multiple comparison procedures
8. Two-way between subjects design
9. Three-way between subjects design
10. One-way within subject design
11. Two-way within subjects design
12. Three-way within subjects design
13. Simple mixed design
14. Complex mixed design: two between-subject factors and one within-subject factor
15. Complex mixed design: one between-subject factor and two within-subject factors
16. Analysis of covariance
17. Advanced topics in analysis of variance
Appendix A. Primer on SPSS
Appendix B. Primer on SAS Enterprise Guide
Appendix C. Table of critical f values
Appendix D. Deviational formula for sums of squares.
Authors
Glenn Gamst, University of La Verne, California
Glenn Gamst is Professor and Chair of the Psychology Department at the University of La Verne, where he teaches the doctoral advanced statistics sequence. He received his PhD from the University of Arkansas in experimental psychology. His research interests include the effects of multicultural variables such as client-therapist ethnic match, client acculturation status and ethnic identity, and therapist cultural competence on clinical outcomes. Additional research interests focus on conversation memory and discourse processing.
Lawrence S. Meyers, California State University, Sacramento
A. J. Guarino is on the faculty at Auburn University, teaching the statistics sequence of ANOVA, multiple regression, MANOVA, and structural equation modeling (SEM) in the College of Education. He received his bachelor's degree from the University of California, Berkeley. He earned a doctorate in statistics and research methodologies from the University of Southern California through the Department of Educational Psychology.
A. J. Guarino, Auburn University, Alabama
Lawrence S. Meyers is Professor of Psychology at Sacramento State University, where he teaches undergraduate and graduate courses in research design, data analysis, data interpretation, testing and measurement, and history and systems of psychology. He received his doctorate from Adelphi University and worked on the National Science Foundation Postdoctoral Fellowship at the University of Texas, Austin, and Purdue University.