Political Science | Topics in Data Analysis: Maximum Likelihood Estimations
Y577 | 26427 | Ensley
This course is primarily concerned with regression analysis of
political phenomena via maximum-likelihood estimation. In many
situations, the Classic Linear Regression Model (CLRM) is unsuitable
for analyzing data that are of interest to political scientists.
This course will introduce students to a set of methods and
techniques for handling situations in which the assumptions of the
CLRM are violated. In particular, the methods employed will consider
techniques for dealing with categorical and limited dependent
variables. Models to be covered include: logit, probit, multinomial
logit, ordered probit, models for event counts (e.g. Poisson
regression), duration models, and survival analysis. We will also
consider models for dealing with “missing” data. Although there will
be emphasis on the technical aspects, most of our attention will be
directed to the application of these methods to political phenomena
and the presentation of the results.
Prerequisites: Y575 and Y576, or their equivalents.