Niko Kaciroti, PhD
- Research Scientist, Biostatistics
- Research Scientist, Pediatrics
- Research Scientist, Center for Computational Medicine and Bioinformatics
Niko Kaciroti received his PhD in Biostatistics from the University of Michigan. Since then he has collaborated in multidisciplinary research at the University of Michigan and with researchers from other universities in the United States and internationally. Dr. Kaciroti’s methodological interest is in using Bayesian models for analyzing multilevel longitudinal data from randomized clinical trials with missing data. He is also interested in using Bayesian methods to model nonlinear and dynamic models in a multilevel setting. His collaborative work centers towards developing and implementing statistical methodologies in pediatric research. Dr. Kaciroti is an elected member of the International Statistical Institute and the Society for Pediatric Research. He serves as the statistical editor for the American Journal of Preventive Medicine and as an associate editor for the International Journal of Behavior Nutrition and Physical Activity. Dr. Kaciroti is a board member for the Pediatric Epilepsy Research Foundation.
American Statistical Association
Internationall Biometric Society
International Statistical Institute
Royal Statistical Society
- PhD, Biostatistics, University of Michigan, 2002
- MSc, Biostatistics, University of Michigan, 1994
- BSc, Applied Mathematics, University of Tirana, 1991
Radesky JS, Kaciroti NA, Weeks HM, Schaller A, Miller AL: Longitudinal associations between use of mobile
devices for calming, emotional reactivity, and executive functioning in young children.
JAMA pediatrics 177(1): 62-70, 2023.
Shafie Khorassani F, Taylor JMG, Kaciroti NA, MR Elliott MR. Incorporating Covariates into Measures of Surrogate Paradox Risk. Stats 6 (1): 322-344, 2023.
Kaciroti NA: Letter to the Editor in response to ‘Z-Score Burden Metric: A Method for Assessing Burden of Injury and Disease’. American Journal of Preventive Medicine 64 (2): 301, 2022.
Kaciroti NA, Little RJA: Bayesian sensitivity analyses for longitudinal data with dropouts that are potentially missing not at random: A high dimensional pattern-mixture model. Stat Med 40(21): 4609- 4628, 2021.
Kaciroti NA, Lumeng C, Parekh V, Boulton ML: A Bayesian Mixture Model for Predicting the COVID-19 Pandemic in the United States. Am J Trop Med Hyg 104(4), 1484-1492, 2021.
Brook RD, Kaciroti NA, Jamerson T, Jamerson KA: Cardiovascular Benefits of Combination Angiotensin- Converting Enzyme Inhibition Plus Calcium Channel Blockade in Black Hypertensive Patients. Hypertension 78(4): 1150-1152, 2021.
Kaciroti N, DosSantos MF, Moura B, Bellile EL, Nascimento TD, Maslowski E, Danciu TE, Donnell A, DaSilva AF: Sensory-Discriminative Three-Dimensional Body Pain Mobile App Measures Versus Traditional Pain Measurement With a Visual Analog Scale: Validation Study. JMIR Mhealth Uhealth 8(8): e17754, 2020.
Shah PE, Weeks HM, Richards B, Kaciroti NA. Early childhood curiosity and kindergarten reading and math academic achievement. Pediatric research 84 (3), 380-386, 2018.
Mosli RH, Kaciroti NA, Corwyn RF, Bradley RH, Lumeng JC: Effect of Sibling Birth on BMI Trajectory in the First 6 Years of Life. Pediatrics 137(4): e20152456, 2016.
Lumeng J, Kaciroti N, Sturza J, Krusky A, Miller A, Peterson K, Lipton R, Reischl T. Changes in body mass index associated with head start participation. Pediatrics 135(2): 449-456, 2015
Kaciroti NA, Raghunathan T: Bayesian sensitivity analysis of incomplete data: bridging pattern-mixture and selection models. Stat Med 33(27): 4841-57, 2014.
Kaciroti NA, Raghunathan TE, Taylor JM, Julius S: A Bayesian model for time-to-event data with informative censoring. Biostatistics 13(2): 341-54, 2012.
Kaciroti NA, Schork MA, Raghunathan T, Julius S: A Bayesian sensitivity model for intention-to-treat analysis on binary outcomes with dropouts. Stat Med 28(4): 572-85, 2009.
Kaciroti NA, Raghunathan TE, Schork MA, Clark NM: A Bayesian model for longitudinal count data with non-ignorable dropout. J R Stat Soc Ser C Appl Stat 57(5): 521-534, 2008.
Julius S, Nesbitt SD, Egan BM, Weber MA, Michelson EL, Kaciroti NA, Black HR, Grimm RH, Messerli FH, Oparil S, Schork MA, Trial of Preventing Hypertension (TROPHY) Study In: Feasibility of treating prehypertension with an angiotensin-receptor blocker., N Engl J Med. 354(16): 1685-1697, 2006.
Kaciroti NA, Raghunathan T, Schork MA, Clark N, Gong M: A Bayesian approach for clustered longitudinal ordinal outcome with nonignorable missing data: Evaluation of an asthma education program. Journal of the American Statistical Association 101: 435-446, 2006.