Journal publications resulting from PSTAT 296A-B and PSTAT 196 Projects
- Duncan I. & Guerrier S., Member Plan Choice and Migration in Response to Changes in Member Premiums after Massachusetts Health Insurance Reform, North American Actuarial Journal, 2016 Dec., 20(4) 404-19.
- Kerr D., Yadollahi M., Mendoza H., Chen X., Dong S., Guerrier S., Laan R., Duncan I., Use of a Publicly Available Database to Determine the Impact of Diabetes on Length of Hospital Stay for Elective Orthopedic Procedures in California, Population Health Management, 2016 Dec., 19(6) 439-444.
- Duncan I, Loginov M, & Ludkovski M., Testing Alternative Regression Frameworks for Predictive Modeling of Health Care Costs, North American Actuarial Journal, 20(1), 1-23, 2016.
Additional research partially supported by SOA CAE 2015 Education Grant
Duncan I., Huynh N., Molinari R., Duncan J., Using Survival Analysis to Predict Workers’ Compensation Termination, Variance, in press.
Duncan I., Huynh N., (2018) A predictive model for re-admissions among Medicare patients in a California Hospital, Population Health Management, 21(4),pp. 317-322.
Goffard, P-O & Lefevre, C.(2018) , Duality in ruin problems for ordered risk models, Insurance: Mathematics and Economics,2018(78), issue C, pp. 44-52.
Goffard, P-O.(2017), Two-sided exit problems in the ordered risk model, Methodology and Computing in Applied Probability. https://doi.org/10.1007/s11009-017-9606-z
Goffard, P-O., & Laub, P., Two Numerical Methods to Evaluate Stop-Loss Premiums, submitted.
Goffard, P-O., & Sarantsev, A., Exponential Convergence Rate of Ruin Probabilities for Level-Dependent Levy-Driven Risk Process, submitted.
Goffard, P-O., Fraud Risk Assessment within Blockchain Transactions, submitted.
Duncan I., Herndon W., Liao X., Health Benefits Associated with an Employer-sponsored Health Promotion Program with Device-reported Activity, under review.
Liao X., Chen G., Ku, B, Narula R. and Duncan J., Text Mining Methods Applied to Insurance Company Customer Calls: A Case Study North American Actuarial Journal, accepted.
Liao X. and Meyer M. (2018), Estimation and Inference in Mixed-Effect Regression Models using Shape Constraints, with Application to Tree Height Estimation, submitted.
Liao X., D. Kerr, J. Morales and I. Duncan (2019). Application of Machine Learning to Identify Modifiable Cardio-Metabolic Risk Factors in U.S. Adults, Diabetes Technology & Therapeutics, 21(5), pp. 245-253. https://www.ncbi.nlm.nih.gov/pubmed/30969131