Analysis of Factors that Influence Member Turnover in a Health Insurance Plan

In this research, we implement a multiple logistic regression model in which the coefficients of indicator variables are constrained to be zero or positive. By doing this, the contribution of each variable to the failure probability can be assessed. Due to this restriction on the coefficients, a Bayesian approach to parameter estimation--which assigns mixture priors to the coefficients--is taken. The data is provided by a large health insurance company in Western Pennsylvania and includes the enrollment status and corresponding values of the 84 predictor variables for 1,280,612 individuals. The insurer feels the analysis is needed to determine why its membership is declining, why its cost trend is higher than the national average, and what logical steps can be taken to reverse the current trends.

Name thesis:degree_name

MS

Level thesis:degree_level

Worldwide Access

Discipline thesis:degree_discipline

Computational Mathematics

Year dc:date.available

2004

Author dc:creator

• Bennett, Sara

Contributors dc:contributor

• John C. Kern
• Constance D. Ramirez
• Frank D'Amico
• Kathleen Taylor
• Richard Pro

• Bayesian
• logistic regression
• MCMC

Language dc:language

English

Repository record dc:identifier

https://dsc.duq.edu/etd/24

OAI identifier oai:identifier

oai:dsc.duq.edu:etd-1023