An edition of Introducing ANOVA and ANCOVA (2000)

Introducing ANOVA and ANCOVA

a GLM approach

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Last edited by Open Library Bot
December 5, 2010 | History
An edition of Introducing ANOVA and ANCOVA (2000)

Introducing ANOVA and ANCOVA

a GLM approach

  • 0 Ratings
  • 2 Want to read
  • 1 Currently reading
  • 0 Have read

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Publish Date
Publisher
SAGE
Language
English
Pages
182

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Previews available in: English

Edition Availability
Cover of: Introducing Anova and Ancova
Introducing Anova and Ancova: A GLM Approach
2010, SAGE Publications, Limited
in English
Cover of: Introducing ANOVA and ANCOVA
Introducing ANOVA and ANCOVA: a GLM approach
2001, SAGE
in English
Cover of: Introducing Anova and Ancova
Introducing Anova and Ancova: a Glm Approach
2000, SAGE Publications, Incorporated
in English

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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.

Published in
London ; Thousand Oaks, Calif
Series
Introducing statistical methods, ISM (London, England)

Classifications

Dewey Decimal Class
519.5/38
Library of Congress
QA279 .R88 2001, QA279.R88 2001

The Physical Object

Pagination
ix, 182 p. :
Number of pages
182

ID Numbers

Open Library
OL3965828M
Internet Archive
introducinganova00ruth
ISBN 10
0761951601, 076195161X
LCCN
2001270786
OCLC/WorldCat
44185265
Goodreads
1249308

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December 5, 2010 Edited by Open Library Bot Added subjects from MARC records.
April 28, 2010 Edited by Open Library Bot Linked existing covers to the work.
December 10, 2009 Created by WorkBot add works page