300 N. Ingalls Bldg. Room 1027NW Ann Arbor, MI 48109
Niko Kaciroti is a Biostatistician whose primary research interest is in analyzing longitudinal and repeated measures data with missing values. He is currently working on developing and using Bayesian models for analyzing longitudinal outcomes with nonignorable missing data. Another area of research is using complex and dynamic models within a hierarchical Bayesian framework to analyze cortisol data. His applied research is focused in the application of statistics in an interdisciplinary setting related to medical, social science and public health fields. This includes, application of advance statistical methods to longitudinal data using linear and nonlinear mixed models, survival analysis and structural equation modeling.
Dr. Kaciroti is actively collaborating with several members of CHGD and is Co-Investigator on a number of large NIH and NSF funded projects. Kaciroti is Director of the Statistical Core for a multi-university program project grant on brain and behavior in early iron deficiency.
Niko Kaciroti has received a grant from RW Johnson Foundation for development of pharmacokinetic-pharmacodynamic (PK/PD) models using Bayesian framework.