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Jason Newsom's
USP 656 Advanced Data Analysis: Multilevel Regression




This course is intended to introduce students to multilevel regression techniques (also known as hierarchical linear models or random coefficient models) and will cover the fundamental concepts and application of the techniques. By the end of the course, students should be able to apply, write about, critique applications of, and read methodological articles about multilevel regression analysis.



Winter 2016 Syllabus
Class syllabus, reading list, and my contact information.



Supplemental Readings
Readings (zip folder)  and some optional readings (zip folder)


Current Homework
Get a copy of the current homework and link to the data sets.


Homework Data Sets
Homework and some class example data sets


Overheads and Handouts
Handouts I've discussed in class and some of the overheads presented in class (pdf unless otherwise noted).

Why MLR?

Regression Review

Multilevel Regression Equations

Distinguishing Between Random and Fixed: Variables, Effects, and Coefficients

Overheads: Between-Group Variance, Within-Group Variance

Raudenbush & Bryk Example Data Set: High School & Beyond

Intercept Only Model Example (Random Effects ANOVA): SPSS, R, HLM

ANCOVA Example (One Level-1 Predictor): SPSS, R, HLM

Artificial Intraclass Correlation Coefficient Example

Plotting Within-Group Regression Lines: SPSS, R, HLM

Overhead: Illustrations of Intercept-Slope Correlations

Significance Testing in Multilevel Regression

Random Effects Test Examples: SPSS, R, HLM

Example R2 Computation

Cross-level Interaction Example (Predicting Random Slopes)

Simple Slope Tests of Cross-level Interactions

Centering in Multilevel Regression

Centering Examples: SPSS and R

Overhead: Centering and Within, Between, and Compositional Effects

Estimation Methods in Multilevel Regression for Continuous Dependent Variables

Robust Standard Errors

Clarification of Notation for Growth Curve Models

Preparing Data Sets for Growth Curve Analysis

Unconditional Growth Curve Examples: SPSS, R, HLM

Time-Invariant Growth Curve Examples: SPSS, R, HLM

Time-Varying Covariate Growth Curve Examples: SPSS, R, HLM

Quadratic Growth Curve Examples: SPSS, R, HLM

Plotting Growth Curves: SPSS, R, HLM

Overhead: Piecewise Growth Curves

Notes on Error Structures in Multilevel and Growth Curve Models

Logistic Regression Review

Multilevel Models with Binary and other Noncontinuous Dependent Variables

Generalized Multilevel Regression Example for a Binary Outcome

Summary of Binary Estimation Options

Missing Data in Multilevel Regression

Sample Size Issues and Power

Further Reading on Multilevel Regression



Stats Notes
Over 20 "Web lectures" on introductory graduate statistics



Snijders & Bosker (2012) book site with data sets and software examples (including Stata, R, & MLwiN)

Paul Bliese's Introduction to Multilevel Regression with R

Hox (first edition) computer examples at UCLA statistical computing site (includes HLM, MLWin, SAS, Stata & R examples)

UCLA site examples for other multilevel texts (see Multilevel Modeling)

UCLA SPSS casestovars and varstocases examples

Singer & Willet's Applied Longitudinal Data Analysis Book

Growth curve examples from the Singer & Willet text (includes SPSS as well as SAS, HLM, MLWin, State, SPlus, Mplus)

HLM 7 Student Version (for the full version and other information, see the HLM main menu at SSI)

HLM Software Rental (rent for 6 months or a year)

HLM Software Examples

Join the multilevel modeling list

A multilevel regression model site at University of Bristol. Information on software, papers, FAQs etc.

Data sets for Joop Hox's text, seond edition (A number of good multilevel resources)

Free multilevel regression software: MIXREG, MIXNO, MIXPREG (by Don Hedeker and Robert Gibbons)

Singer's Using SAS Proc Mixed article

Bristol Center for Multilevel Modeling (online learning modules and many useful resources)

Free Copy of Harvey Goldstein's Multilevel Book

Optimal Design Power Software (free)