|Title:||Introduction to Choice Modeling|
|Presenter:||Meghan Cain, Senior Statistician, StataCorp|
|Date:||Tuesday, 31 May 2022|
|Time:||12:15 to 12:45 p.m.|
Discrete choice models are used across disciplines to analyze choice behavior. For example, voters choose their candidate or party, commuters choose a mode of transportation, college freshmen choose majors, and employers choose job candidates. In all of these cases, we observe decision making entities that are faced with a set of alternatives to choose from. Discrete choice models with alternative-specific variables allow for including variables that can vary both over decision makers as well as choice sets. In other words, we can incorporate attributes of the decision maker as well as attributes of the alternatives into our analysis.
In recent years, it has become apparent that psychological factors, such as emotional states, attitudes, and personality characteristics, are important attributes of the decision maker that need to be considered when modeling many types of choices. This talk will provide a quick introduction to choice modeling and a demonstration of fitting and interpreting choice models in Stata.
Meghan Cain is a Senior Statistician at StataCorp. She earned her PhD in quantitative psychology from the University of Notre Dame, where her research focused on structural equation modeling, multilevel modeling, and Bayesian statistics. At Stata, she develops and presents training on these and other topics. She also conducts webinars, works with developers to produce Stata documentation, and contributes to Stata blogs.
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