Varying Coefficients in Logistic Regression with Applications to Marketing Research

In the marketing research world today, companies have access to massive amounts of data regarding the purchase behavior of consumers. Researchers study this data to understand how outside factors, such as demographics and marketing tools, affect the probability that a given consumer will make a purchase. Through the use of panel data, we tackle these questions and propose a logistic regression model in which coefficients can vary based on a consumer's purchase history. We also introduce a two-step procedure for model selection that uses a group LASSO penalty to decide which are informative and which variables need varying coefficients in the model.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Statistics

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2012

Author dc:creator

• Condon, Erin

Contributors dc:contributor

• He, Xuming
• Douglas, Jeffrey A.
• Qu, Peiyong
• Martinsek, Adam T.

• varying coefficients
• group LASSO
• marketing research
• logistic regression
• Least Absolute Selection and Shrinkage Operator (LASSO)

Statement dc:rights

• Copyright 2012 Erin Condon

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/30947

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/30947