Arman Sabbaghi, Ph.D.
Associate Professor of Statistics at Purdue University
Contact Information
Purdue University Department of Statistics
150 North University Street
West Lafayette, IN 47907-2066
Office: MATH 204
E-mail: sabbaghi@purdue.edu
Phone: (765) 496-0234
Home | Curriculum Vitæ | Teaching | Google Scholar | ResearchGate | LinkedIn
Education
PhD, Statistics, Harvard University, 2014
AM, Statistics, Harvard University, 2011
BS, Mathematics (With Honors), Purdue University, 2009
BS, Mathematical Statistics, Purdue University, 2009
News
- May 20, 2024: Best Application Paper at the 2024 Institute of Industrial and Systems Engineering (IISE) Annual Conference & Expo.
- May 15, 2024: Chair-Elect 2025 of the Section on Physical and Engineering Sciences (est. 1954) of the American Statistical Association.
- December 2022: Winner of a Seed for Success Acorn Award.
- August 19-20, 2022: 2022 Purdue Krannert-Statistics Causal Machine Learning for Novel Settings Boot Camp.
- July 13-15, 2021: 2021 Purdue Krannert-Statistics Machine Learning and Causal Inference Boot Camp.
- June 18, 2021: Program Chair-Elect 2022 of the Section on Physical and Engineering Sciences (est. 1954) of the American Statistical Association.
- December 17, 2020: Elected Member of the International Statistical Institute.
Recent Manuscripts
- Ross J.L., Sabbaghi A., Zhang R., Bertolini D., the Alzheimer's Disease Cooperative Study, the Alzheimer's Disease Neuroimaging Initiative, the Critical Path for Alzheimer's Disease, the European Prevention of Alzheimer's Disease (EPAD) Consortium, the Pooled Resource Open-Access ALS Clinical Trials Consortium (2024). Enhancing longitudinal clinical trial efficiency with digital twins and prognostic covariate-adjusted mixed models for repeated measures (PROCOVA-MMRM). arXiv.
- Li Y., Sabbaghi A., Walsh J.R., Fisher C.K. (2024). Prognostic covariate adjustment for logistic regression in randomized controlled trials. arXiv.
- Vanderbeek A.M., Sabbaghi A., Walsh J.R., Fisher C.K. (2024). Bayesian prognostic covariate adjustment with additive mixture priors. arXiv.
- Ohnishi Y., Karmakar B., Sabbaghi A. (2024). Degree of interference: A general framework for causal inference under interference. Journal of Machine Learning Research (accepted).
- Patel S.H., Campbell N.W.C., Emenim C.E., Farino D.O., Damen F.W., Rispoli J.V., Goergen C.J., Haus J.M., Sabbaghi A., Carroll C.C. (2024). Patellar tendon biomechanics in pre-diabetes and type 2 diabetes patients. Journal of Orthopaedic Research 42, 1653-1669. DOI: 10.1002/jor.25816.
- Ohnishi Y., Sabbaghi A. (2024). A Bayesian analysis of two-stage randomized experiments in the presence of interference, treatment nonadherence, and missing outcomes. Bayesian Analysis 19:1, 205-234. DOI: 10.1214/22-BA1347.
- Nieforth L.O., Rodriguez K., Zhuang R., Miller E.A., Sabbaghi A., Schwichtenberg A.J., Granger D.A., O'Haire M.E. (2024). The cortisol awakening response in a three-month clinical trial of service dogs for veterans with posttraumatic stress disorder. Scientific Reports 14:1, 1664.
- Abdul Wahab A.H., Qu Y., Michelis H., Luo J., Zhuang R., McDaniel D., Xi D., Polverejan E., Gilbert S., Ruberg S., Sabbaghi A. (2024). Clinical Trials With Intercurrent Events Simulator (CITIES). Biometrical Journal 66:1, 2200103.
- Vanderbeek A.M., Vidovszky A.A., Ross J.L., Sabbaghi A., Walsh J.R., Fisher C.K., the Critical Path for Alzheimer's Disease, the Alzheimer's Disease Neuroimaging Initiative, the European Prevention of Alzheimer's Disease (EPAD) Consortium, the Alzheimer's Disease Cooperative Study (2023). A weighted prognostic covariate adjustment method for efficient and powerful treatment effect inferences in randomized controlled trials. arXiv.
- Leighton S.C., Rodriguez K.E., Zhuang R., Jensen C.L., Miller E.A., Sabbaghi A., O'Haire M.E. (2023). Psychiatric service dog placements are associated with better daily psychosocial functioning for military veterans with PTSD. Psychological Trauma: Theory, Research, Practice, and Policy Jul 6:10.1037/tra0001543.
- Carroll C.C., Campbell N.W.C., Patel S.H., Ferrandi P., Couture S., Farino D.O., Stout J., Sabbaghi A. (2023). Impact of essential amino acid intake, resistance exercise, and aging on Achilles peritendinous amino acid concentrations and collagen synthesis. Amino Acids 55:6, 777-787. DOI: 10.1007/s00726-023-03268-3.
- Geng Z., Sabbaghi A., Bidanda B. (2023). Automated variance modeling for three-dimensional point cloud data via Bayesian neural networks. IISE Transactions 55:9, 912-925. DOI: 10.1080/24725854.2022.2106389 (Featured Research Article in August 2023 Industrial and Systems Engineer Magazine).
- Geng Z., Sabbaghi A., Bidanda B. (2023). Reconstructing original design: Process planning for reverse engineering. IISE Transactions 55:5, 509-522. DOI: 10.1080/24725854.2022.2040761 (Best Application Paper in the 2023 IISE Transactions Focus Issue on Design and Manufacturing).
- Zhang Y., Sabbaghi A. (2022). Distributed design for causal inferences on Big Observational Data. arXiv.
- Geng Z., Sabbaghi A., Bidanda B. (2022). A framework of tolerance specification for freeform point clouds and capability analysis for reverse engineering processes. International Journal of Production Research (Special issue of "Editorial Board contributions celebrating the 60th Anniversary of IJPR") 60:24, 7475-7491.
- Jensen C.L., Rodriguez K.E., MacLean E.L., Wahab A.H.A., Sabbaghi A., O'Haire M.E. (2022). Characterizing veteran and PTSD service dog teams: Exploring potential mechanisms of symptom change and canine predictors of efficacy. PLoS One 17(7): e0269186.
- Keaton T.J., Sabbaghi A. (2022). Dismemberment and design for controlling the risk of regret for the multi-armed bandit. Journal of Statistical Theory and Practice (AISC-2021 Special Collection) 16:55, 1-29.
- Nieforth L.O., Abdul Wahab A.H., Sabbaghi A., Wadsworth S.M., Foti D., O'Haire M.E. (2022). Quantifying the emotional experiences of partners of veterans with PTSD service dogs using ecological momentary assessment. Complementary Therapies in Clinical Practice 48: 101590.