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Robert Crosnoe, Chair CLA 3.306, Mailcode A1700, Austin, TX 78712 • 512-232-6300

Spring 2010

SOC 386L • Dynamic Models and Longitudinal Data Analysis

Unique Days Time Location Instructor
46530 MW
3:30 PM-5:00 PM
RAS 313A

Course Description

This is a course in statistical methods for longitudinal data analysis. We will cover two main content areas: multiple regression models for data collected on the same subjects over time (repeated measures/panel data), and methods for modeling event occurrences over time.

Multilevel/Hierarchical Models for Change
The first half of the course introduces multilevel models for change (i.e., growth curve models), which are appropriate for the analysis of change in a continuous dependent variable over time. Given this general exposure to the topic, students should be able to apply multilevel modeling techniques to any substantive research problem. We will review latent linear growth curve models from the perspective of structural equation modeling (SEM). Growth curve models for categorical outcomes (counts), as well as nonlinear growth curve models, will also be discussed.

Event History Analysis
The second half of this course deals with event history analysis (i.e., survival analysis, hazard models, etc.), which is a technique for modeling the probability of a transition from one status (or state) to another. We will focus on discrete time and continuous time models that make few assumptions regarding time dependence of the hazard (i.e., semiparametric methods, such as the piecewise constant exponential and the Cox proportional hazard model). We will focus mainly on single transition models.

Students should have taken a previous course in linear regression.

Grading Policy

This is an applied course. We will learn by applying the techniques learned in class to specific pedagogical examples in approximately 5 assignments. No previous programming experience is required. We will use several statistical packages in this course depending on the problem: Stata, SAS, and R. Examples will be provided in each package.


J. D. Singer, and J. B. Willett, Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence, New York: Oxford University Press, (2003)
We will use a combination of textbook and handouts posted to Bb.


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