Joop Hox, Mirjam Moerbeek, Rens van de Schoot
Multilevel Analysis
Techniques and Applications, Third Edition
Joop Hox, Mirjam Moerbeek, Rens van de Schoot
Multilevel Analysis
Techniques and Applications, Third Edition
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Applauded for its clarity, this accessible text helps readers apply multilevel techniques to their research.
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Applauded for its clarity, this accessible text helps readers apply multilevel techniques to their research.
Produktdetails
- Produktdetails
- Verlag: Routledge
- 3rd edition
- Seitenzahl: 348
- Erscheinungstermin: 14. September 2017
- Englisch
- Abmessung: 229mm x 152mm x 21mm
- Gewicht: 658g
- ISBN-13: 9781138121409
- ISBN-10: 1138121401
- Artikelnr.: 50433269
- Verlag: Routledge
- 3rd edition
- Seitenzahl: 348
- Erscheinungstermin: 14. September 2017
- Englisch
- Abmessung: 229mm x 152mm x 21mm
- Gewicht: 658g
- ISBN-13: 9781138121409
- ISBN-10: 1138121401
- Artikelnr.: 50433269
Joop J. Hox is Emeritus Professor of Social Science Methodology at Utrecht University, the Netherlands. Mirjam Moerbeek is Associate Professor of Statistics for the Social Sciences at Utrecht University, the Netherlands. Rens van de Schoot is an Associate Professor of Bayesian Statistics at Utrecht University, the Netherlands, and Extra-Ordinary Professor at the North-West University, South Africa.
1. Introduction to Multilevel Analysis 2. The Basic Two-Level Regression
Model. 3. Estimation and Hypothesis Testing in Multilevel Regression. 4.
Some Important Methodological and Statistical Issues 5. Analyzing
Longitudinal Data. 6. The Multilevel Generalized Linear Model for
Dichotomous Data and Proportions. 7. The Multilevel Generalized Linear
Model for Categorical and Count Data. 8. Multilevel Survival Analysis. 9.
Cross-Classified Multilevel Models. 10. Multivariate Multilevel Regression
Models. 11. The Multilevel Approach to Meta-Analysis. 12. Sample Sizes and
Power Analysis in Multilevel Regression. 13. Assumptions and Robust
Estimation Methods. 14. Multilevel Factor Models. 15. Multilevel Path
Models. 16. Latent Curve Models. Appendices.
Model. 3. Estimation and Hypothesis Testing in Multilevel Regression. 4.
Some Important Methodological and Statistical Issues 5. Analyzing
Longitudinal Data. 6. The Multilevel Generalized Linear Model for
Dichotomous Data and Proportions. 7. The Multilevel Generalized Linear
Model for Categorical and Count Data. 8. Multilevel Survival Analysis. 9.
Cross-Classified Multilevel Models. 10. Multivariate Multilevel Regression
Models. 11. The Multilevel Approach to Meta-Analysis. 12. Sample Sizes and
Power Analysis in Multilevel Regression. 13. Assumptions and Robust
Estimation Methods. 14. Multilevel Factor Models. 15. Multilevel Path
Models. 16. Latent Curve Models. Appendices.
1. Introduction to Multilevel Analysis 2. The Basic Two-Level Regression
Model. 3. Estimation and Hypothesis Testing in Multilevel Regression. 4.
Some Important Methodological and Statistical Issues 5. Analyzing
Longitudinal Data. 6. The Multilevel Generalized Linear Model for
Dichotomous Data and Proportions. 7. The Multilevel Generalized Linear
Model for Categorical and Count Data. 8. Multilevel Survival Analysis. 9.
Cross-Classified Multilevel Models. 10. Multivariate Multilevel Regression
Models. 11. The Multilevel Approach to Meta-Analysis. 12. Sample Sizes and
Power Analysis in Multilevel Regression. 13. Assumptions and Robust
Estimation Methods. 14. Multilevel Factor Models. 15. Multilevel Path
Models. 16. Latent Curve Models. Appendices.
Model. 3. Estimation and Hypothesis Testing in Multilevel Regression. 4.
Some Important Methodological and Statistical Issues 5. Analyzing
Longitudinal Data. 6. The Multilevel Generalized Linear Model for
Dichotomous Data and Proportions. 7. The Multilevel Generalized Linear
Model for Categorical and Count Data. 8. Multilevel Survival Analysis. 9.
Cross-Classified Multilevel Models. 10. Multivariate Multilevel Regression
Models. 11. The Multilevel Approach to Meta-Analysis. 12. Sample Sizes and
Power Analysis in Multilevel Regression. 13. Assumptions and Robust
Estimation Methods. 14. Multilevel Factor Models. 15. Multilevel Path
Models. 16. Latent Curve Models. Appendices.