I work primarily on statistical methods with medical applications. I have particular interest in models for longitudinal data (especially counts and other non-normal responses), survival time models, parameter-driven models, random effects, and latent variables. I have worked extensively in the field of hidden Markov models. Most recently, I have been working on random survival forests and assessing prediction error in survival times.  I have applied my research to problems in fields such as multiple sclerosis and ovarian cancer.

Selected Publications

Berkowitz M, Altman RM, and Loughin TM (2024). Random forests for survival data: which methods work best and under what conditions? Int J Biostat.

Altman RM, Harari O, Moisseeva N, Steyn D (2023). Statistical Modelling of the Annual Rainfall Pattern in Guanacaste, Costa Rica. Water. 15(4): 700.

Berkowitz M, Altman RM (2022). A bivariate longitudinal cluster model with application to the Cognitive Reflection Test. The Quantitative Methods for Psychology. 28(1): 21-38. 

McKerracher LJ, Nepomnaschy PA, Altman RM, Sellen D, Collard M (2020). Breastfeeding durations and the social learning of infant feeding knowledge in two Maya communities. Human Nature. 31: 43-67. 

Hoi AG, Daiy K, Altman RM, Venners S, Valeggia C, Nepomnaschy P (2020). Postpartum amenorrhea duration by sex of the newborn in two natural fertility populations. American Journal of Physical Anthropology. 174(4): 661-669.