The aim of this course is to expand your portfolio of tools for data anal-ysis. Maximum likelihood methods open the door wide for a variety of substantive areas of interest. We will not be able to cover everything over the course of the semester, but you should leave this class equipped with the tools necessary to learn new methods on your own.
We will cover a lot of material over the course of the semester. Below are a list of topics (those noted with asterisks may be covered depending on interest and available time).
- Maximum Likelihood Theory
- Generalized Linear Models
- Models for dichotomous variables
- Models for ordinal variables
- Models for categorical variables
- Introduction to Hierarchical Models (*)
- Introduction to Duration/Survival Modeling (*)
- Introduction to Bayesian Inference (*)
The course is designed to give you the foundational tools required to understand and implement maximum likelihood techniques. For sev-eral of the topics, especially those covered in the latter part of the class, standalone courses exist and there is enough material to fill up an entire semester. My aim in this course is to give you a set of tools that will allow you to pick up new methods.