About me

I am an Assistant Professor in the Statistics Department at UC Berkeley. My research centers on methodology for causal inference in observational studies. I develop new ways to form matched comparison groups in large observational datasets using approaches from discrete optimization. These tools allow transparent and interpretable inferences about the effects of interventions, and provide opportunities to study the impact of potential unobserved confounding variables. I am also interested in applying these methods in health services research, public policy, and the social sciences.




Huang, M., and Pimentel, S.D. (2023+). Variance-based sensitivity analysis for weighting estimators results in more informative bounds. arxiv:2208.01691. Won 2023 Best Theory Poster Award from the Society for Political Methodology.

Pimentel, S.D. (2023+). Covariate-adaptive randomization inference for matched designs. arxiv:2207.05019.

Soriano, D., Ben-Michael, E., Bickel, P.J., Feller, A., and Pimentel, S.D. (2023+). Interpretable sensitivity analysis for balancing weights. arxiv:2102.13218.


Statistical Methodology

Glazer, A.K., and Pimentel, S.D. (2023+). Robust inference for matching under rolling enrollment. Journal of Causal Inference (in press). arxiv:2205.01061.

Howard, S.R., and Pimentel, S.D. (2021). The uniform general signed rank test and its design sensitivity. Biometrika 108, 381-396. arXiv:1904.08895.

Pimentel, S.D., and Kelz, R.R. (2020). Optimal tradeoffs in matched designs comparing US-trained and internationally trained surgeons. Journal of the American Statistical Association 115 (532), 1675-1688. Download

Pimentel, S.D., Forrow, L.V., Gellar, J., and Li, J. (2020). Optimal matching approaches in health policy evaluations under rolling enrolment. Journal of the Royal Statistical Society - Series A 183 (4), 1411-1435. Download

Keele, L., Harris, S., Pimentel, S.D., and Grieve, R. (2020). Stronger instruments and refined covariate balance in an observational study of the effectiveness of prompt admission to the ICU in the UK. Journal of the Royal Statistical Society - Series A 183 (4), 1501-1521. Download

Keele, L., and Pimentel, S.D. (2019). Matching with attention to effect modification in a data challenge. Observational Studies 5, 83-92.

Pimentel, S.D., Page, L., Lenard, M., and Keele, L. (2018). Optimal multilevel matching using network flows: an application to a summer reading intervention. Annals of Applied Statistics, 12:3, 1479-1505. Download

Pimentel, S.D., Small, D.S. , and Rosenbaum, P.R. (2017). An exact test of fit for the Gaussian linear model using optimal nonbipartite matching. Technometrics, 59 (3), 330-337. Download

Pimentel, S.D., Small, D.S., and Rosenbaum, P.R. (2016). Constructed second control groups and attenuation of unmeasured biases. Journal of the American Statistical Association, 111 (515), 1157-1167. Download

Pimentel, S.D., Kelz, R.R., Silber, J.H., and Rosenbaum, P.R. (2015). Large, sparse optimal matching with refined covariate balance in an observational study of the health outcomes produced by new surgeons. Journal of the American Statistical Association, 110 (510), 515-527. Download

Pimentel, S.D., Yoon, F., and Keele, L. (2015). Variable-ratio matching with fine balance in a study of the Peer Health Exchange. Statistics in Medicine, 34 (30), 4070-4082. Download

Statistical Applications

Kuzniewicz, M.W., Campbell, C.I., Li, S., Walsh, E.M., Croen, L.A., Comer, S.D., Pimentel, S.D., Hedderson, M. and Sun, L.S. (2022). Accuracy of diagnostic codes for prenatal opioid exposure and neonatal opioid withdrawal syndrome . Journal of Perinatology, 1-7.

Silber, J.H., Rosenbaum, P.R., Pimentel, S.D., Calhoun, S., Wang, W., Sharpe, J.E., Reiter, J.G., Shah, S.A., Hochman, L.A., and Even-Shoshan, O. (2019). Comparing resource use in medical admissions of children with complex chronic conditions. Medical Care, 57 (8), 615-624.

Zaheer, S., Pimentel, S.D., Simmons, K.D., Kuo, L.E.Y, Datta, J., Williams, N., Fraker, D.L., and Kelz, R.R. (2017). Comparing international and United States undergraduate medical education and surgical outcomes using a refined balance methodology. Annals of Surgery, 265 (5), 916-922.

Grossman, G., Gazal-Ayal, O., Pimentel, S.D., and Weinstein, J. (2016). Descriptive representation and judicial outcomes in multi-ethnic societies. American Journal of Political Science, 60 (1), 44-69. doi:10.1111/ajps.12187.

Software for Statistics and Data Visualization

Pimentel, S.D. (2016). Large, sparse optimal matching with R package rcbalance. Observational Studies, 2, 4-23.

Pimentel, S.D., and Keele, L. (2016). R package matchMulti: Optimal Multilevel Matching using a Network Algorithm. Published on The Comprehensive R Archive Network.

Pimentel, S.D. (2016). R package rcbsubset: Optimal Subset Matching with Refined Covariate Balance. Published on The Comprehensive R Archive Network.

Pimentel, S.D. (2014). R package rcbalance: Large, Sparse Optimal Matching with Refined Covariate Balance. Published on The Comprehensive R Archive Network.

Pimentel, S.D. (2014). Choosing a clustering: an a posteriori method for social networks. Journal of Social Structure Vol. 15, No. 1.

Pimentel, S., Walbot, V., and Fernandes, J. (2011). GRFT – genetic records family tree web applet. Frontiers in Genetics 2.