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
Race, J. and Pennell, M.L. (2020). Semi-parametric survival analysis via Dirichlet Process mixtures of the first hitting time model. Lifetime Data Analysis. In press.
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.
Erich, R. and Pennell, M.L. (2015). Ornstein-Uhlenbeck threshold regression models for time to event data with and without a cure fraction. Lifetime Data Analysis. 21, 1-19.
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