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ANOVA and ANCOVA [[electronic resource] ] : a GLM approach / / Andrew Rutherford
ANOVA and ANCOVA [[electronic resource] ] : a GLM approach / / Andrew Rutherford
Autore Rutherford Andrew <1958->
Edizione [2nd ed.]
Pubbl/distr/stampa Hoboken, NJ, : Wiley, c2011
Descrizione fisica 1 online resource (360 p.)
Disciplina 519.538
Soggetto topico Analysis of variance
Analysis of covariance
Linear models (Statistics)
ISBN 1-118-49168-8
1-283-59290-8
9786613905352
1-118-49171-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto ANOVA and ANCOVA A GLM Approach; Contents; Acknowledgments; 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; 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; 2.2 Balanced Data Designs; 2.3 Factors and Independent Variables; 2.4 An Outline of Traditional ANOVA for Single Factor Designs; 2.5 Variance; 2.6 Traditional ANOVA Calculations for Single Factor Designs; 2.7 Confidence Intervals; 2.8 GLM Approaches to Single Factor ANOVA; 2.8.1 Experimental Design GLMs; 2.8.2 Estimating Effects by Comparing Full and Reduced Experimental Design GLMs; 2.8.3 Regression GLMs
2.8.4 Schemes for Coding Experimental Conditions 2.8.4.1 Dummy Coding; 2.8.4.2 Why Only (p - 1) Variables Are Used to Represent All Experimental Conditions?; 2.8.4.3 Effect Coding; 2.8.5 Coding Scheme Solutions to the Overparameterization Problem; 2.8.6 Cell Mean GLMs; 2.8.7 Experimental Design Regression and Cell Mean GLMs; 3 Comparing Experimental Condition Means, Multiple Hypothesis Testing, Type 1 Error, and a Basic Data Analysis Strategy; 3.1 Introduction; 3.2 Comparisons Between Experimental Condition Means; 3.3 Linear Contrasts; 3.4 Comparison Sum of Squares; 3.5 Orthogonal Contrasts
3.6 Testing Multiple Hypotheses 3.6.1 Type 1 and Type 2 Errors; 3.6.2 Type 1 Error Rate Inflation with Multiple Hypothesis Testing; 3.6.3 Type 1 Error Rate Control and Analysis Power; 3.6.4 Different Conceptions of Type 1 Error Rate; 3.6.4.1 Test wise Type 1 Error Rate; 3.6.4.2 Family wise Type 1 Error Rate; 3.6.4.3 Experiment wise Type 1 Error Rate; 3.6.4.4 False Discovery Rate; 3.6.5 Identifying the ""Family"" in Family wise Type 1 Error Rate Control; 3.6.6 Logical and Empirical Relations; 3.6.6.1 Logical Relations; 3.6.6.2 Empirical Relations; 3.7 Planned and Unplanned Comparisons
3.7.1 Direct Assessment of Planned Comparisons 3.7.2 Contradictory Results with ANOVA Omnibus F-tests and Direct Planned Comparisons; 3.8 A Basic Data Analysis Strategy; 3.8.1 ANOVA First?; 3.8.2 Strong and Weak Type 1 Error Control; 3.8.3 Step wise Tests; 3.8.4 Test Power; 3.9 The Three Basic Stages of Data Analysis; 3.9.1 Stage 1; 3.9.2 Stage 2; 3.9.2.1 Rom's Test; 3.9.2.2 Shaffer's R Test; 3.9.2.3 Applying Shaffer's R Test After a Significant F-test; 3.9.3 Stage 3; 3.10 The Role of the Omnibus F-Test; 4 Measures of Effect Size and Strength of Association, Power, and Sample Size
4.1 Introduction
Record Nr. UNINA-9910141423003321
Rutherford Andrew <1958->  
Hoboken, NJ, : Wiley, c2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
ANOVA and ANCOVA [[electronic resource] ] : a GLM approach / / Andrew Rutherford
ANOVA and ANCOVA [[electronic resource] ] : a GLM approach / / Andrew Rutherford
Autore Rutherford Andrew <1958->
Edizione [2nd ed.]
Pubbl/distr/stampa Hoboken, NJ, : Wiley, c2011
Descrizione fisica 1 online resource (360 p.)
Disciplina 519.538
Soggetto topico Analysis of variance
Analysis of covariance
Linear models (Statistics)
ISBN 1-118-49168-8
1-283-59290-8
9786613905352
1-118-49171-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto ANOVA and ANCOVA A GLM Approach; Contents; Acknowledgments; 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; 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; 2.2 Balanced Data Designs; 2.3 Factors and Independent Variables; 2.4 An Outline of Traditional ANOVA for Single Factor Designs; 2.5 Variance; 2.6 Traditional ANOVA Calculations for Single Factor Designs; 2.7 Confidence Intervals; 2.8 GLM Approaches to Single Factor ANOVA; 2.8.1 Experimental Design GLMs; 2.8.2 Estimating Effects by Comparing Full and Reduced Experimental Design GLMs; 2.8.3 Regression GLMs
2.8.4 Schemes for Coding Experimental Conditions 2.8.4.1 Dummy Coding; 2.8.4.2 Why Only (p - 1) Variables Are Used to Represent All Experimental Conditions?; 2.8.4.3 Effect Coding; 2.8.5 Coding Scheme Solutions to the Overparameterization Problem; 2.8.6 Cell Mean GLMs; 2.8.7 Experimental Design Regression and Cell Mean GLMs; 3 Comparing Experimental Condition Means, Multiple Hypothesis Testing, Type 1 Error, and a Basic Data Analysis Strategy; 3.1 Introduction; 3.2 Comparisons Between Experimental Condition Means; 3.3 Linear Contrasts; 3.4 Comparison Sum of Squares; 3.5 Orthogonal Contrasts
3.6 Testing Multiple Hypotheses 3.6.1 Type 1 and Type 2 Errors; 3.6.2 Type 1 Error Rate Inflation with Multiple Hypothesis Testing; 3.6.3 Type 1 Error Rate Control and Analysis Power; 3.6.4 Different Conceptions of Type 1 Error Rate; 3.6.4.1 Test wise Type 1 Error Rate; 3.6.4.2 Family wise Type 1 Error Rate; 3.6.4.3 Experiment wise Type 1 Error Rate; 3.6.4.4 False Discovery Rate; 3.6.5 Identifying the ""Family"" in Family wise Type 1 Error Rate Control; 3.6.6 Logical and Empirical Relations; 3.6.6.1 Logical Relations; 3.6.6.2 Empirical Relations; 3.7 Planned and Unplanned Comparisons
3.7.1 Direct Assessment of Planned Comparisons 3.7.2 Contradictory Results with ANOVA Omnibus F-tests and Direct Planned Comparisons; 3.8 A Basic Data Analysis Strategy; 3.8.1 ANOVA First?; 3.8.2 Strong and Weak Type 1 Error Control; 3.8.3 Step wise Tests; 3.8.4 Test Power; 3.9 The Three Basic Stages of Data Analysis; 3.9.1 Stage 1; 3.9.2 Stage 2; 3.9.2.1 Rom's Test; 3.9.2.2 Shaffer's R Test; 3.9.2.3 Applying Shaffer's R Test After a Significant F-test; 3.9.3 Stage 3; 3.10 The Role of the Omnibus F-Test; 4 Measures of Effect Size and Strength of Association, Power, and Sample Size
4.1 Introduction
Record Nr. UNINA-9910826581903321
Rutherford Andrew <1958->  
Hoboken, NJ, : Wiley, c2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui