Multilevel Analysis: Techniques and ApplicationsPsychology Press, 2002 - 304 pagina's This book is an introduction to multilevel analysis for applied researchers featuring models for hierarchical or nested data. This book presents two types of models: The multilevel regression and multilevel covariance structures models. Despite the book being an introduction, it includes a discussion of many extensions and special applications. As an introduction, it will be useable in courses in a variety of fields, such as psychology, education, sociology, and business. The various extensions and special applications make it useful to researchers who work in applied or theoretical research, and to methodologists that have to consult with these researchers. The basic models and examples are discussed in non-technical terms; the emphasis is on understanding the methodological and statistical issues involved in using these models. Some of the extensions and special applications contain more technical discussions, either because that is necessary for understanding what the model does, or as an introduction to more advanced treatments. Thus, the book will be useful as an introduction and as a standard reference for a large variety of applications. |
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Pagina vii
... bootstrap 189 11.4 Bayesian estimation methods 191 11.4.1 Simulating the posterior distribution 193 11.4.2 An example of Bayesian estimation using MlwiN: the estrone data 193 11.4.3 An example of Bayesian estimation using MlwiN: the ...
... bootstrap 189 11.4 Bayesian estimation methods 191 11.4.1 Simulating the posterior distribution 193 11.4.2 An example of Bayesian estimation using MlwiN: the estrone data 193 11.4.3 An example of Bayesian estimation using MlwiN: the ...
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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 |
References | 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 |
Veelvoorkomende woorden en zinsdelen
analyze approach assume asymptotic Bayesian bootstrap Bosker Chapter chi-square test coeff compute confidence interval covariance matrix cross-classified cross-level interaction data set deviance dummy variables estrone example data explanatory variables factor family level Figure fixed Goldstein group level 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 models multilevel regression model multiple regression 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 Wald test zero