GOV 385L • Advanced Statistical Analysis
11:00 AM-12:30 PM
In this course we will study some advanced statistical analyses, including models with categorical or limited dependent variable, event count models, event history models, models for time-series cross-section data, and models for hierarchical data. Most of these models rely on the maximum likelihood method of estimation, and hence we will first discuss probability distributions and statistical estimation theory, with an emphasis on the MLE. We will use STATA for statistical analysis and MAPLE for symbolic algebra.
You are required to write a research paper based on a statistical procedure introduced in this class. The topic of the paper is your own choice, but you should discuss your ideas with the instructor early in the semester to obtain his approval. Depending on substantive merits, topics based "simplistic" methods may not be acceptable. By Week 8, you should turn in a paper proposal (5-10 pages) laying out your theoretical arguments, describing your data, and presenting your research design. You should work closely with the instructor in developing ideas, formulating models, acquiring data, and carrying out the analyses. Your grade will be based on the end result as well as your interaction with the instructor while working on this paper. There may be homework assignments and/or exams as the instructor deems necessary.
* W. H. Greene. 2003. Econometric Analysis. 5th ed. Prentice Hall. * G. King.1998. Political Methodology: The Likelihood Theory of Statistical Inference. Michigan. * S. R. Eliason. 1993. Maximum Likelihood Estimation: Logic and Practice. Sage. * A packet of journal articles and book chapters. Optional: * J. M. Box-Steffensmeier and B. S. Jones. 2004. Event History Analysis. Cambridge. * T. F. Liao. 1994. Interpreting Probability Models. Sage. * D. A. Luke. 2004. Multilevel Modeling. Sage.