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Analysis of Variance Designs - A Conceptual and Computational Approach with SPSS and SAS
Glenn Gamst, Lawrence S. Meyers and A. J. Guarino
Cambridge University Press
November 2008
Hardback 594 pp ISBN 9780521874816
£45.00
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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
Contents
- ANOVA and research design
- Measurement, central tendency, and variability
- Elements of ANOVA
- The statistical significance and effect of strength
- Analysis of variance assumptions
- One-way between subjects design
- Multiple comparison procedures
- Two-way between subjects design
- Three-way between subjects design
- One-way within subject design
- Two-way within subjects design
- Three-way within subjects design
- Simple mixed design
- Complex mixed design: two between-subject factors and one within-subject factor
- Complex mixed design: one between-subject factor and two within-subject factors
- Analysis of covariance
- 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
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