An edition of Introducing ANOVA and ANCOVA
(2000)
Introducing ANOVA and ANCOVA
a GLM approach
by Andrew Rutherford
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Subjects
Analysis of covariance, Analysis of variance| Edition | Availability |
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1
Introducing Anova and Ancova: A GLM Approach
2010, SAGE Publications, Limited
in English
1412933358 9781412933353
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Introducing Anova and Ancova: a Glm Approach
2000, SAGE Publications, Incorporated
in English
1280369302 9781280369308
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Book Details
Table of Contents
Machine generated contents note: 1 AN INTRODUCTION TO GENERAL LINEAR MODELS: REGRESSION, ANALYSIS
OF VARIANCE AND ANALYSIS OF COVARIANCE
1.1 Regression, analysis of variance and analysis of covariance
1.2 A pocket history of regression, ANOVA and ANCOVA
1.3 An outline of general linear models (GLMs)
1.3.1 Regression analysis
1.3.2 Analysis of variance
1.3.3 Analysis of covariance
1.4 The "general" in GLM
1.5 The "linear" in GLM
1.6 Least squares estimates
1.7 Fixed, random and mixed effects analyses
1.8 The benefits of a GLM approach to ANOVA and ANCOVA
1.9 The GLM presentation
1.10 Statistical packages for computers
2 TRADITIONAL AND GLM APPROACHES TO INDEPENDENT MEASURES SINGLE
FACTOR ANOVA DESIGNS
2.1 Independent measures designs
2.1.1 Factors and independent variables
2.2 Traditional ANOVA for single factor designs
2.2.1 Variance
2.2.2 Example
2.3 GLM approaches to single factor ANOVA
2.3.1 Experimental design GLMs
2.3.2 Estimating effects by comparing full and reduced experimental
design GLMs
2.3.3 Regression GLMs
2.3.4 Cell mean GLMs
2.3.5 Cell mean, regression and experimental desigh GLMs
3 GLM APPROACHES TO INDEPENDENT MEASURES FACTORIAL ANOVA
DESIGNS
3.1 Factorial designs
3.2 Factor main effects and factor interactions
3.2.1 Estimating effects by comparing full and reduced experimental
design GLMs
3.3 Regression GLMs for factorial ANOVA
3.3.1 Estimating main and interaction effects with regression GLMs
4 GLM APPROACHES TO REPEATED MEASURES DESIGNS
4.1 Related measures designs
4.2 Repeated measures designs
4.3 Order effect controls
4.3.1 Counterbalancing
4.3.2 Randomization
4.4 The GLM approach to single factor repeated measures designs
4.5 Estimating effects by comparing full and reduced single factor repeated
measures design GLMs
4.6 Regression GLMs for single factor repeated measures designs
5 GLM APPROACHES TO FACTORIAL REPEATED MEASURES DESIGNS
5.1 Factorial related measures designs
5.2 The fully related factorial design GLM
5.3 Estimating effects by comparing full and reduced fully related factorial
experimental design GLMs
5.4 Regression GLMs for the fully related factorial ANOVA
5.5 Mixed factorial ANOVA
5.6 Estimating effects by comparing full and reduced mixed factorial
experimental design GLMs
5.7 Regression GLM for the mixed factorial ANOVA
6 THE GLM APPROACH TO ANCOVA
6.1 The nature of ANCOVA
6.2 Single factor independent measures ANCOVA designs
6.3 Estimating effects by comparing full and reduced single factor
independent measures ANCOVA GLMs
6.4 Regression GLMs for the single factor independent measures
ANCOVA
6.5 Other ANCOVA designs
6.5.1 Related measures ANCOVA designs
6.5.2 Mixed measures factorial ANCOVA
7 ASSUMPTIONS UNDERLYING ANOVA, TRADITIONAL ANCOVA AND GLMS
7.1 ANOVA and GLM assumptions
7.1.1 Independent measures
7.1.2 Related measures
7.1.3 Traditional ANCOVA
7.2 A strategy for checking ANOVA and traditional ANCOVA assumptions
7.3 Assumption checks and some assumption violation consequences
7.3.1 ANOVA and ANCOVA
7.3.2 Traditional ANCOVA
8 SOME ALTERNATIVES TO TRADITIONAL ANCOVA
8.1 Alternatives to traditional ANCOVA
8.2 The heterogeneous regression problem
8.3 The heterogeneous regression ANCOVA GLM
8.4 Single factor independent measures heterogeneous regression
ANCOVA
8.5 Estimating heterogeneous regression ANCOVA effects
8.6 Regression GLMs for heterogeneous ANCOVA
8.7 Covariate-experimental condition relations
8.7.1 Multicollinearity
8.8 Other alternatives
8.8.1 Stratification (blocking)
8.8.2 Replacing the experimental conditions with the covariate
8.9 The role of ANCOVA
9 FURTHER ISSUES IN ANOVA AND ANCOVA
9.1 Power
9.1.1 Optimal experimental designs
9.1.2 Normality violations
9.1.3 Main effects and interactions
9.2 Error rate and the omnibus F-tests
9.3 Error rate and multiple comparisons
9.4 The role of the omnibus F-test
REFERENCES
INDEX.
Edition Notes
Includes bibliographical references (p. [173]-177) and index.
Index sheets need inserting.
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History
- Created April 1, 2008
- 13 revisions
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