Michael Pennell, PhD

Dr. Pennell's research interests include nonparametric Bayes, first hitting time models for survival analysis, design and analysis of Group Randomized Trials, joint modeling outcomes of different scales, statistical methods in toxicological risk assessment, and statistical applications in biomedical research including cancer control, pathology, and veterinary medicine.

Design and analysis of group randomized trials, first hitting time models for survival analysis, Bayesian nonparametrics, joint modeling, toxicological risk assessment

• PhD, Biostatistics, University of North Carolina at Chapel Hill, 2006
• MS, Biostatistics, University of North Carolina at Chapel Hill, 2002
• BS, Biology, University of Puget Sound, 2000

Lim, W., Pennell, M.L., Naughton, M.J., and Paskett, E.D. (2023). Bayesian semiparametric joint modeling of a count outcome and inconveniently timed longitudinal predictors. Statistical Methods in Medical Research. 32, 853-867.

Lim, W., Pennell, M.L., Naughton, M.J., and Paskett, E.D. (2022). Bayesian semiparametric joint modeling of longitudinal explanatory variables of mixed types and a binary outcome. Statistics in Medicine. 41, 17-36.

Race, J. and Pennell, M.L. (2021). Semi-parametric survival analysis via Dirichlet Process mixtures of the first hitting time model. Lifetime Data Analysis. 27, 177-194.

Nattino, G., Pennell, M.L., and Lemeshow, S. (2020). Assessing the goodness of fit of logistic regression models in large samples: a modification of the Hosmer-Lemeshow Test. Biometrics. 76, 549-560.

Hwang, B.S. and Pennell, M.L. (2018). Semiparametric Bayesian joint modeling of clustered binary and continuous outcomes with informative cluster size in developmental toxicity assessment.  Environmetrics. 29, e2526.

Xi, W., Pennell, M.L., Andridge, R.A., and Paskett, E.D. (2018).Comparison of intent-to-treat strategies for pre-post studies with loss to follow-up.  Contemporary Clinical Trials Communications.  11, 20-29.