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Introducing ANOVA and ANCOVA : a GLM approach / Andrew Rutherford.

By: Material type: TextTextSeries: ISM (London, England)Publication details: London ; Thousand Oaks, Calif. : SAGE, 2001.Description: ix, 182 p. : ill. ; 25 cmISBN:
  • 0761951601
  • 076195161X (pbk.)
Subject(s): DDC classification:
  • 519.538 21 RUT
LOC classification:
  • QA279 .R88 2001
Online resources:
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.
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Item type Current library Collection Call number Status Date due Barcode
Schedule Reference Materials Schedule Reference Materials Main Library Reference Section Schedule Reference Collection 519.538RUT (Browse shelf(Opens below)) Available 38073

Index sheets need inserting.

Includes bibliographical references (p. [173]-177) and index.

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.

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