Adam Ciarleglio
Adam Ciarleglio
M.S., Ph.D.
Associate Professor
School: Milken Institute School of Public Health
Department: Biostatistics and Bioinformatics
Contact:
Email:
Adam Ciarleglio
Office Phone:
(202)-994-9879
Science & Engineering Hall
800 22nd Street, NW
Washington DC 20052
Dr. Ciarleglio is an Associate Professor of Biostatistics in the Department of Biostatistics and Bioinformatics. He is broadly interested in integrating functional data analysis, machine learning, and treatment regime estimation methods to address questions in public health and medical research, especially those related to mental health. He completed a postdoctoral research fellowship in the Division of Biostatistics in the Department of Child and Adolescent Psychiatry at the New York University School of Medicine in 2016. Prior to joining GWU, he was a faculty member in the Division of Mental Health Data Science at the New York State Psychiatric Institute and the Department of Biostatistics at the Mailman School of Public Health at Columbia University.
EXPERTISE:
Biostatistics
Mental Health
EDUCATION:
BA Mathematics, Vanderbilt University, 2005
MS Mathematics, Fairfield University, 2008
PhD Biostatistics, Columbia University, 2013
INSTITUTES AND CENTERS:
Dr. Ciarleglio is an affiliated with the following:
Biostatistics and Epidemiology Consulting Service (BECS): The Biostatistics and Epidemiology Consulting Service (BECS) provides biostatistical and epidemiologic support to improve the quality of health-related research conducted at the George Washington University and by affiliated research groups. We provide support through consultations, extended collaborative relationships, communication about best practices, and broad-based services in research design, statistical analysis, data management, and dissemination of findings.
The Biostatistics Center: The Biostatistics Center provides leadership and expertise in the execution of clinical trials, observational studies, and diagnostic studies; fosters biostatistical science by developing and implementing innovative approaches for the design, conduct, analysis, and reporting of clinical research studies; and provide training and education relevant to clinical trials and other clinical research.
GW Institute for Brain Health and Dementia: The Institute aims to promote and support research on cognitive health that will meaningfully impact lives, through promotion of brain health, prevention of cognitive loss, addressing disparities in cognitive health, and improving the quality of life of persons living with dementia and their care partners.
GW Cancer Center: The Center's mission is to drive transformational research, personalized therapy, family-centered care, and cancer policy in the nation’s capital.
RESEARCH:
Dr. Ciarleglio is currently PI of NIH/NIA grant R25 AG081177 Expanding the Pipeline to Graduate Research in Alzheimer's Disease and Related Dementias (EPGRAD) Program (Apr 2023 - Jan 2028)
Dr. Ciarleglio recently completed grant NIH/NIMH - K01 MH113850 Statistical and Machine Learning Methods for Integrating Clinical and Multimodal Imaging Data to Select Optimal Antidepressant Treatment (Sept 2018 - Aug 2023)
PUBLICATIONS:
A complete list of publications is available at my Google Scholar page.
Selected Statistical Methodology Papers
- Ciarleglio, A., Petkova, E., Harel, O. Elucidating age and sex-dependent association between frontal EEG asymmetry and depression: An application of multiple imputation in functional regression. Journal of the American Statistical Association. (2022) 117(537): 12 - 26.
- Ciarleglio, A., Petkova, E., Tarpey, T., Ogden, R. T. Constructing treatment decision rules based on scalar and functional predictors when moderators of treatment effect are unknown. Journal of the Royal Statistical Society: Series C. (2018) 67(5): 1331 - 1356.
- Ciarleglio, A., Petkova, E., Tarpey, T., Ogden, R. T. Flexible functional regression methods for estimating individualized treatment regimes. Stat. (2016) 5: 185 - 199.
- Ciarleglio, A., Ogden, R. T. Wavelet-based scalar-on-function finite mixture regression models. Computational Statistics & Data Analysis. (2016) 93: 86 - 96.
- Ciarleglio, A., Petkova, E., Ogden, R. T, Tarpey, T. Treatment decisions based on scalar and functional baseline covariates. Biometrics. (2015) 71 (4): 884 - 894.
Selected Clinical Papers
- Power, M., Bennett, E., Turner, R., Dowling, M., Ciarleglio, A., Glymour, M., Gianattasio, K. Trends in Relative Racial Disparities in the Incidence and Prevalence of Dementia in the United States, 2000-2016. JAMA Neurology. (2021) 78(3): 275 – 284.
- Ciarleglio, A., Brucato, G., Masucci, M., Altschuler, R., Appelbaum, P., Colibazzi, T., Corcoran, C., Crump, F., Horga, G., Lehembre-Shiah, E., Leong, W., Schobel, S., Wall, M., Yang, L., Lieberman, J., Girgis, R. A predictive model for conversion to psychosis in clinical high-risk patients. Psychological Medicine. (2019) 49: 1128 - 1137.
- Brewster, K., Ciarleglio, A., Chen, C., Brown, P., Rutherford, B. Age-related hearing loss and its association with depression in later life. The American Journal of Geriatric Psychiatry. (2018) 26 (7): 788 - 796.
- Girgis, R., Ciarleglio, A., Choo, T., Haynes, G., Bathon, J., Cremers, S., Kantrowitz, J., Lieberman, J., Brown, A. A randomized, double-blind, placebo-controlled clinical trial of tocilizumab, an interleukin-6 receptor antibody, for residual symptoms in schizophrenia. Neuropsychopharmacology. (2018) 43: 1317–1323.
- Anderson, B., Ciarleglio, A., Hayes, D., Friedman, R., Bacha, E. Earlier arterial switch operation improves outcomes and reduces costs for neonates with transposition of the great arteries. Journal of the American College of Cardiology. (2014) 63 (5): 481 - 487.
PUBH 6865 Applied Categorical Data Analysis for Public Health Research
PUBH 6886 Statistical and Machine Learning for Public Health Research