Feng-Chang Lin, PhD
Feng-Chang Lin, PhD
Serving as a biostatistician in the Translational and Clinical Sciences Institute (TraCS) at the University of North Carolina at Chapel Hill, Dr. Lin is heavily engaged in collaborative research in biomedical fields.
His primary area of research lies in the development of novel statistical methods for modeling recurrent events that frequently appear in biomedical studies. These methodologies aim to assist physicians and healthcare providers in better understanding the natural history of a disease and its risk factors.
Honors and AwardsTeaching Innovation Award
2018-2019, Gillings School of Global Public HealthStudy Abroad Scholarship
2005-2006, Ministry of Education, Taiwan
Probability and Statistical Inference II (BIOS 661/673)
Research ActivitiesDr. Lin is a biostatistician in the North Carolina Translational and Clinical Sciences Institute (NC TraCS), home of the UNC-CH Clinical and Translational Science Awards (CTSA). His research interests include:
Generalized linear model
Prevention clinical trials
Genetics in Medicine (2012-2018)
Journal of the American Statistical Association (JASA)
Journal of the Royal Statistical Society, Series B (JRSSB)
Statistics in Medicine
From 2011 - 2013, Dr. Lin served as the principal, then the vice principal, of the North Carolina Raleigh Chinese Language School, a registered nonprofit organization founded in 1977. The school originally specialized in teaching Mandarin and traditional Chinese characters, but now offers 20 language classes and 12 culture classes for 200 students.
Effect of calories-only vs physical activity calorie expenditure labeling on lunch calories purchased in worksite cafeterias. Viera A.J., Gizlice Z., Tuttle L., Olsson E., Gras-Najjar J., Hales D., Linnan L., Lin F.C., Noar S.M., and Ammerman A. (2019). BMC Public Health, 19(1), 107.
Multi-state models of transitions in depression and anxiety symptom severity and cardiovascular events in patients with coronary heart disease. Meyer M.L., Lin F.C., Jaensch A., Mons U., Hahmann H., Koenig W., Brenner H., and Rothenbacher D. (2019). PLoS One, 14(3).
Analysis of clustered failure time data with cure fraction using copula. Su C.L. and Lin F.C. (2019). Statistics in Medicine, 38(21), 3961-3973.
Triggered palliative care for late-stage dementia: a pilot randomized trial. Hanson L.C., Kistler C., Lavin K., Gabriel S.L., Ernecoff N.C., Lin F.C., Sachs G.A., and Mitchell S.L. (2019). Journal of Pain and Symptom Management, 57(1), 10-19.
The effect of numeracy level on completeness of home blood pressure monitoring. Rao V.N., Sheridan S.L., Tuttle L.A., Lin F.C., Shimbo D., Diaz K.M., Hinderliter A.L., Viera A.J. (2015). Journal of Clinical Hypertension, 17(1), 39-45.
Levels of office blood pressure and their operating characteristics for detecting masked hypertension based on ambulatory blood pressure monitoring. Viera, A.J.; Lin, F-C; Tuttle, L.A.; Shimbo, D.; Diaz, K.M.; Olsson, E.; Stankevitz, K.; Hinderliter, A.L. (2015). American Journal of Hypertension, 28(1), 42-49.
PhD, Statistics, University of Wisconsin, Madison, 2008
MA, Statistics, University of Wisconsin, Madison, 2006