This course is an elective in the clinical psychology Ph.D. program.
The class was first offered during the 2015/2016 school year. I used SPSS and Mplus; while background through and including multivariate statistics (i.e., Statistics II at RFUMS), no knowledge of statistics packages is assumed (some students have experience with LISREL, whereas others worked with Mplus). The plan is to offer this course every other spring.
The course focuses on longitudinal modeling. Modeling will be done from a structural equation modeling perspective (SEM), multilevel modeling (MLM) and generalized estimating equation (GEE) approaches, as well as to techniques with which people are more familiar (i.e., t-tests, regressions, analyses of variance [ANOVAs]).
E-mail me your thoughts!
Subsequent offerings are available through D2L.
Spring, 2016
Little, T. D. (2013). Longitudinal structural equation modeling. New York: The Guilford Press.
Articles:
Enders, C. K. (2001). A primer on maximum likelihood algorithms available for use with missing data. Structural Equation Modeling, 8(1), 128-141. (pdf)
Graham, J. W. (2009). Missing data analysis: Making it work in the real world. Annual Review of Psychology, 60, 549-576. (pdf)
McArdle, J. J., & Hamagami, F. (2001). Latent difference score structural equation models for linear dynamic analysis. In L. M. Collins & A. G. Sayer (eds.). New methods for the analysis of change. (pp. 139-175). Washington, DC, US: American Psychological Association. (pdf)
Preacher, K. J., Zyphur, M. J., & Zhang, Z. (2010). A general multilevel SEM framework for assessing multilevel mediation. Psychological Methods, 15, 209-233.
My multilevel structural equation modeling resources site
Assignments:
Homework 25%
Exam: 25%
Presentation 25%
Final Paper 25%
Calendar
See Hard Copy
Enders, C. K. (2001). A primer on maximum likelihood algorithms available for use with missing data. Structural Equation Modeling, 8(1), 128-141. (pdf)
Graham, J. W. (2009). Missing data analysis: Making it work in the real world. Annual Review of Psychology, 60, 549-576. (pdf)
McArdle, J. J., & Hamagami, F. (2001). Latent difference score structural equation models for linear dynamic analysis. In L. M. Collins & A. G. Sayer (eds.). New methods for the analysis of change. (pp. 139-175). Washington, DC, US: American Psychological Association. (pdf)
Some Files
Data File for Day 1 (SPSS)
Info Sheet from Syllabus
Data File for Day 1 (Mplus)
Input
Output
Other
Final Exam Assigned