Jason
Newsom's
USP
656 Advanced Data Analysis:
Multilevel Regression
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Description
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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. |
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Winter 2013 Syllabus
Click
here for the class
syllabus, reading list, and my contact information.
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Supplemental Readings
Readings
(zip folder)
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Current Homework
Get a
copy of the current homework
and link to the data sets.
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Homework Data Sets
Homework
and some class example data
sets
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Overheads and Handouts
Handouts I've discussed in
class and some of the overheads presented in class (pdf
unless otherwise noted).
Overhead:
Multilevel Overview Figures
Overhead:
Within-Group Variance
Overhead:
Between-Group Variance
Distinguishing
Between Random and Fixed: Variables, Effects, and Coefficients
High School and
Beyond Data Description
ANOVA
and ANCOVA Examples: SPSS and HLM
Intraclass Correlation Coefficient
Overhead:
Intercept-Slope Correlation Illustrations
Plotting
Within-Group Regression Lines In SPSS and HLM
Significance
Testing in Multilevel Regression
Excel
Sheet for Mixture Chi-Square with LR Test
Model Fit Indices
for Non-Nested Models
Cross-Level
Interaction Example
Simple
Slopes for Cross-Level Interactions
Overhead:
Compositional Effect
Estimation
Methods in Multilevel Regression for Continuous Dependent Variables
Missing Data
in Multilevel Regression
Clarification
of Notation for Growth Curve Models
Preparing
Data Sets for Growth Curve Analysis
Plotting
Growth Curves in SPSS and HLM
Multilevel
Models with Binary and other Noncontinuous Dependent
Variables
Regression Models
for Ordinal Dependent Variables
Estimation
Methods in Non-continuous Multilevel Regression
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Stats Notes
Over 20
"Web
lectures" on introductory graduate statistics
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Links
Snijders
& Bosker (2012) book site with data sets and
software examples (including Stata, R, & MLwiN)
Paul Bliese's Introduction to Multilevel Regression with R
Multilevel
Regression with Stata
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
Craig Enders (Arizona
State) Restructuring
data with SPSS pull-down menus
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)
Join
the multilevel modeling list
A multilevel
regression model site at University of Bristol. Information
on software, papers, FAQs etc.
Joop Hox (A number of good multilevel resources)
Basic concepts in HLM with
applications for policy analysis (online article by Willms,
1999)
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)
John Painter's SPSS Mixed Examples
Optimal
Design Power Software (free)
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