Research Associate II
Dr. Coman is a seasoned statistician with expertise in complex designs and analyses, with particular application in analyzing health disparities and comparing effectiveness of interventions and treatments from a patient centered perspective. His main focus is on precise and reliable systematic measurement of health related outcomes, dealing with data and modeling challenges to ensure sound causal conclusions that can inform policy, and answering specific health disparities and comparative effectiveness questions about delivery of equitable health care. His interests center on statistically assessing evidence and translating it to providers. He has worked on projects like developing patient and provider versions of Care Coordination measures, utilizing peer-supporters to help diabetic patients, the development of a Health Disparities/Equity hospital dashboard, and preventing diabetes in at risk racial/ethnic minorities. He specializes in latent variable modeling (or SEM), evaluation of intervention effects (e.g., with propensity score matching and complier average causal effects models), complex issues of measurement (scales vs. indices, dichotomous indicators), longitudinal and dynamical modeling, models with feedback loops, social network analysis, mixture analysis (unobserved/latent groupings), and simple and modern causal mediation.
Blake, H., Suggs, L. S., Coman E. , Aguirre, L., Batt M. E. (2015). Active8! Technology-based intervention to promote physical activity in hospital employees. American Journal of Health Promotion. Pubmed.
Coman, E. N., Suggs, L. S., Iordache, E., Coman, M. A., & Fifield, J. (2015). A Review of Graphical Approaches to Common Statistical Analyses. The Omnipresence of Latent Variables in Statistics International Journal of Clinical Biostatistics and Biometrics, 1(1), 1-9. Pubmed.
Zlateva, I., Anderson, D., Coman, E., Khatri, K., Tian, T., & Fifield, J. (2015). Development and validation of the Medical Home Care Coordination Survey for assessing care coordination in the primary care setting from the patient and provider perspectives. BMC Health Services Research, 15(1), 226, Pubmed.
Wu, Z. H., Tennen, H., Hosain, G. M. M., Coman, E., Cullum, J., & Berenson, A. B. (2014). Stress Mediates the Relationship Between Past Drug Addiction and Current Risky Sexual Behaviour Among Low-income Women. Stress and Health, n/a-n/a. doi: 10.1002/smi.2587.
Coman, E., Lin, C., Suggs, S., Iordache, E., Barbour, R. (2014). Altering dynamic pathways to reduce substance use among youth: change achieved by dynamic coupling. Addiction Research & Theory, doi:10.3109/16066359.2014.892932.
Coman, E., Picho, K., McArdle, J. J., Villagra, V., & Dierker, L. (2013). The paired t-test as a simple model with a latent change score. Frontiers in Quantitative Psychology and Measurement, 4, Article 738, doi: 10.3389/fpsyg.2013.00738.
Coman, E., Iordache, E., Dierker, L., Fifield, J., Schensul, J. J., Suggs, S., et al. (2014, May). Statistical power of alternative structural models for comparative effectiveness research: advantages of modeling unreliability. Journal of Modern Applied Statistical Methods. rejected by Prevention Science (2011) & by Health Education & Behavior (2012) as ‘Evaluating community-based youth prevention interventions by comparing alternative models: decision-trees for testing and sorting modeling assumptions’.
Coman, E., Weeks, M.R., Yanovitzky, I., Iordache, E., Barbour, R., Coman, M.A., Huedo-Medina, T. (2012). The impact of information about the female condom on female condom use among males and females from a US urban community. AIDS and Behavior, 17(6):2194-201. doi: 10.1007/s10461-012-0381-0.
Coman, E., Iordache, E., Coiculescu, I., Schensul, J. Comparisons of CES-D depression scoring methods in two older adults ethnic groups. The emergence of an ethnic specific brief three-item CES-D scale. International Journal of Geriatric Psychiatry, 28(4), 424–432. doi: 10.1002/gps.3842.