Alla Sikorskii
Department of Psychiatry

Michigan State University
909 Wilson Road, Room 321-A
East Lansing, MI 48824
United States

(517) 432-1737

Alla Sikorskii, PhD


Dr. Alla Sikorskii is a methodologist and statistician with nearly two decades of experience in health research. She has formal training in Statistics and Probability and a track record of successful productive collaboration with health researchers and clinicians. She has built a program of research in symptom management and patient-reported outcomes (PROs) and design and evaluation of interventions to improve these outcomes among people with chronic conditions. Her contributions to PRO measurement and intervention research have been nationally and internationally recognized.

Dr. Sikorskii has designed numerous randomized controlled trials (RCTs) including procedures for screening, randomization, timing of longitudinal assessments, measurement of important confounders, and ways to control for them. Her most recent work is devoted to the advance from traditional RCTs that test fixed interventions to adaptive interventions tailored to individuals. This shift requires research that sequences interventions and creates decision rules for switching from one intervention to another based on individuals’ demonstrated needs. When an intervention does not initially work, clinical logic is to either extend the timeframe or move to a more intensive intervention. This logic leads to multi-staged interventions, where the subsequent stage is individually tailored, based on the response to the previous intervention (stage). Currently, such clinical decisions are not evidence-based. The sequential multiple assignment randomized trial (SMART) allows to build the evidence base for multi-staged interventions. Dr. Sikorskii is leading the applications of the SMART design to test sequences of supportive care interventions among people with chronic conditions. She is also applying advanced stochastic processes methods to identify individuals at risk for adverse quality of life outcomes and those in need for supportive care interventions based on biomarker data including electroencephalogram recordings.





Meerschaert M. M., Sikorskii A. Stochastic Models for Fractional CalculusDe Gruyter, Studies in Mathematics 43, De Gruyter, Berlin, 2012, ISBN 978—3-11-025869-1.

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