Multilevel Analysis: Techniques and ApplicationsRoutledge, 2002 - 320 pagina's An introductory level bk for applied researchers. It assumes that readers have a basic knowledge of social science statistics, including analysis of variance & multiple regression. The book has been used in several multilevel courses including one at the |
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Pagina iv
... Statistical methods. 2. Analysis of variance. 3. Regression analysis. I. Title. HA29.H783 2002 001.4!22–dc21 2001057760 ISBN 1-4106-0411-X Master e-book ISBN Preface Contents 1. Introduction to multilevel analysis 1 1.1. 1.2. Copyright.
... Statistical methods. 2. Analysis of variance. 3. Regression analysis. I. Title. HA29.H783 2002 001.4!22–dc21 2001057760 ISBN 1-4106-0411-X Master e-book ISBN Preface Contents 1. Introduction to multilevel analysis 1 1.1. 1.2. Copyright.
Pagina v
Techniques and Applications Joop Hox. Preface. Contents. 1. Introduction to multilevel analysis 1 1.1. 1.2. 1.3. Why do we need special multilevel analysis ... regression models 2.4.1 Multiple-level models 2.4.2 Intraclass-correlations in ...
Techniques and Applications Joop Hox. Preface. Contents. 1. Introduction to multilevel analysis 1 1.1. 1.2. 1.3. Why do we need special multilevel analysis ... regression models 2.4.1 Multiple-level models 2.4.2 Intraclass-correlations in ...
Pagina vii
... regression models 142 9.1 The basic model 142 9.2 Example of multivariate multilevel analysis: multiple response variables 146 9.3 Example of multivariate multilevel analysis: measuring group characteristics 10. Sample sizes and power ...
... regression models 142 9.1 The basic model 142 9.2 Example of multivariate multilevel analysis: multiple response variables 146 9.3 Example of multivariate multilevel analysis: measuring group characteristics 10. Sample sizes and power ...
Pagina viii
... analysis 12.2.2 Goodness of fit using the ... analysis 13.2 Statistical and software issues in multilevel factor and path models 14. Latent curve models 14.1 Example of latent curve modeling 14.2 A brief comparison of multilevel regression ...
... analysis 12.2.2 Goodness of fit using the ... analysis 13.2 Statistical and software issues in multilevel factor and path models 14. Latent curve models 14.1 Example of latent curve modeling 14.2 A brief comparison of multilevel regression ...
Pagina ix
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Inhoudsopgave
1 Introduction to Multilevel Analysis | 1 |
Introduction | 10 |
3 Estimation and Hypothesis Testing in Multilevel Regression | 34 |
4 Some Important Methodological and Statistical Issues | 45 |
5 Analyzing Longitudinal Data | 66 |
6 The Logistic Model for Dichotomous Data and Proportions | 93 |
7 CrossClassified Multilevel Models | 112 |
8 The Multilevel Approach to MetaAnalysis | 126 |
11 Advanced Methods for Estimation and Testing | 179 |
12 Multilevel Factor Models | 204 |
13 Multilevel Path Models | 227 |
14 Latent Curve Models | 238 |
Data and Stories | 249 |
254 | |
272 | |
282 | |
9 Multivariate Multilevel Regression Models | 142 |
10 Sample Sizes and Power Analysis in Multilevel Regression | 157 |
Overige edities - Alles bekijken
Multilevel Analysis: Techniques and Applications, Second Edition Joop J. Hox,Mirjam Moerbeek,Rens van de Schoot Gedeeltelijke weergave - 2010 |
Multilevel Analysis: Techniques and Applications, Second Edition Joop J. Hox,Mirjam Moerbeek,Rens van de Schoot Gedeeltelijke weergave - 2010 |
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analyze approach assume asymptotic Bayesian bootstrap Chapter chi-square test coeff compute confidence interval covariance matrix cross-classified cross-level interaction data set deviance dummy variables effect estrone example data explained variance explanatory variables factor family level Figure fixed Goldstein group level group mean indicates individual level intercept-only model interpretation intraclass correlation iterations latent curve model level variance linear model logit lowest level MANOVA Maximum Likelihood estimation MCMC meta-analysis MLwiN MPLUS multilevel analysis multilevel model multilevel regression model Muthén nested normal distribution occasions outcome variable p-value parameter estimates plot predictor problem procedure pupil gender pupil level random slopes random-effects model regression analysis regression coefficients regression slopes repeated measures residual error response rate scale school level scores secondary schools significant simulated Snijders specific standard errors statistical structural equation modeling Table teacher experience transformation values variance components variance estimates variation Wald test zero