Latent Variable Models in
the Social Sciences
Multilevel and Structural
Equation Modeling Working Group
Organizer: Dan Bauer ([email protected])
Time: Wednesdays
Location: NISS building, 2nd floor conference
room
Link to password protected
files
Agenda
2/2 IRT as Mixed Model
Rijmen, Frank et al. (2003) �A Nonlinear Mixed
Model Framework for Item Response Theory,�
Psychological Methods, 8(2): 185-205. [pdf file]
1/26 IRT/SEM
Comparison; Multilevel IRT
Kamata, Akihito. (2001)
�Item Analysis by the Hierarchical Generalized Linear Model,�
�Journal
of Educational Measurement, 38(1): 79-93. [pdf file]
Handouts
RJ Wirth. 2PL IRT
vs. polychoric SEM simulations. [pdf file]
Edwards & Wirth.
�Clarification of the Relationship Between CFA and
IRT� [pdf
file]
1/19 Item Response Theory
Thissen, David and Maria Orlando.� �Item Response Theory for Items Scored in Two
Categories.� [pdf file]
Mislevy, Robert J. �Recent Developments in the Factor
Analysis of Categorical Variables.� [pdf file]
12/2
Rabe-Hesketh, S., A. Skrondal, and A. Pickles. 2004. Generalized multilevel structural equation modeling. Psychometrika 69(2) 167--190. [pdf file]
11/18
Readings
Skrondal, A. & Rabe-Hesketh,
S. (2004). Genearlized Latent Variable Modeling
(Chapter 4). Chapman & Hall/CRC:
11/11
Bauer, D.J. 2003.
Estimating multilevel linear models as structural equation models. Journal
of Educational and Behavioral Statistics 28 135--167.
[pdf
file]
Curran, P.J.
2003. Have multilevel models been structural equation models all along? Multivariate
Behavioral Research 38 529--569.
[pdf
file]
10/27
Raudenbush, S., Rowan, B., and Kang, S. (1991). �A Multilevel, Multivariate Model for Studying School Climate with Estimation via the EM Algorithm and Application to U.S. High-School Data,� Journal of Educational Statistics 16(4): 295-330.
Raudenbush, S. and Sampson, R. (1999). �Assessing Direct and Indirect Effects in Multilevel Designs with Latent Variables,� Sociological Methods and Research 28(2): 123-153.
10/14
Continuation of the WinBUGS analysis using the Raudenbush examples. Please refer to these graphical summaries: [graphs.pdf]
10/7
WinBUGS demonstration using the same data from Raudenbush.
Supporting files for the WinBUGS demonstration: [bugs.tar.gz]
Note: The above zipped file contains AppendixC.ps, a tutorial on fitting hierarchical models in R and WinBUGS taken from Bayesian Data Analysis by Gelman, Carlin, Stern, and Rubin.
Other helpful resources:
http://www.stat.columbia.edu/~gelman/bugsR/
http://www.mrc-bsu.cam.ac.uk/bugs/
9/30
Readings:
Raudenbush, Stephen and Bryk, Anthony. Hierarchical Linear Models, 2nd edition. Sage, 2002: Ch. 1-4.
Hox, Joop. Multilevel Analysis: Techniques and Applications. Lawrence Erlbaum, 2003, Ch. 1-2 (optional).
Analysis:
Reproduce Tables 4.2-4.5 in Raudenbush & Bryk using software of choice.
Notes:
http://www.u.arizona.edu/~bsjones/ricetutorial.pdf is a guide to MLM in SAS and Stata using Raudenbush examples.
http://www.ats.ucla.edu/stat/stata/examples/mlm_ma_hox/ reproduces Hox examples in HLM, MLwiN, SAS, and Stata.
9/23
Organizational meeting