Construction of Disease Risk Scoring Systems Using Logistic Group LASSO: Application to Porcine Reproductive and Respiratory Syndrome Survey Data

• Activity Number: 607
• Type: Topic Contributed
• Date/Time: Thursday, August 4, 2011 : 8:30 AM to 10:20 AM
• Sponsor: Section on Risk Analysis
• Author(s): Hui Lin*+ and Chong Wang and Peng Liu and Derald Holtkamp
• Companies: Iowa State University and Iowa State University and Iowa State University and Iowa State University
• Keywords: area under the curve ; group lasso ; risk scoring system ; multivariate logistic regression ; PRRS ; ROC curve

Abstract

We propose to utilize the group lasso algorithm for logistic regression to construct risk scoring systems for predicting diseases which is motivated by the need to develop a risk scoring system from survey data for PRRS which is a disease with major health, production and financial implication for swine producers in nearly every country. Group Lasso provides an attractive solution to this research question because of its ability to select variable groups and achieve parameter stabilization at the same time. We propose to choose the penalty parameter for group lasso through leave-one-out cross validation, using the criterion of the area under the receiver operating characteristic curve. Survey data for 896 swine breeding herd sites in the United States and Canada completed between March 2005 and March 2009 is used to construct the risk scoring system for predicting PRRS outbreaks in swine. We show that our scoring system for PRRS significantly improves the current scoring system which is based on expert opinion. We also show our scoring system is superior in terms of area under the curve to that developed by using another approach in the literature.