Multilevel Analysis with HLM

St. Petersburg: Higher School of Economics, 2011. — 50 p.
Content.
Short Description of the Fictitious Data Used for the Example Analyses.
Traditional Approaches to Multilevel Analysis.
Separate Equations Approach.
Single Equation Approach (OLS Regression).
Slopes as Outcomes Approach.
Multilevel Analysis (2 Level Model).
ANOVA Model (Random Effect ANOVA).
ntraclass Correlation Coefficient.
Random Intercept and Fixed Slope.
Random Intercept and Random Slope.
Multilevel Model with Cross-Level Interaction Terms.
Multilevel Model with Cross-Level Interaction Terms.
Multilevel Model with Cross-Level Interaction Terms (Final Model).
Comparison: OLS-Regression and Multilevel Analysis.
nteraction Effects.
nterpretation of Interaction Effects.
t-Values for Conditional Effects.
Chi-Square-Test for Variance Components.
Empirical Bayes Estimators and Reliability of j ˆ Yi.
Explained Variance: R2 for Level 1 and Level 2.
Fit Measures for Model Comparison.
Standardized Regression Coefficients in Models with Interaction Terms.
Logistic Regression.
References.
App. 1: Full HLM-Output for the ANOVA Model (Chapter 3.1).
App. 2: Full HLM-Output for the Model in Chapter 3.5.1.
App. 3: Example Multilevel Logistic Regression 50.
В пособии рассказывается, как обрабатывать данные в программе HLM.