McAnulty College and Graduate School of Liberal Arts
John C. Kern
Constance D. Ramirez
Bayesian, logistic regression, MCMC
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.
Bennett, S. (2004). Analysis of Factors that Influence Member Turnover in a Health Insurance Plan (Master's thesis, Duquesne University). Retrieved from https://dsc.duq.edu/etd/24