Jasjeet Sekhon
Jasjeet Sekhon
Eugene Meyer Professor of Data Science, Political Science, and Statistics, Yale University
Verified email at - Homepage
Cited by
Cited by
Multivariate and propensity score matching software with automated balance optimization: the matching package for R
JS Sekhon
Journal of Statistical Software, Forthcoming, 2008
Genetic matching for estimating causal effects: A general multivariate matching method for achieving balance in observational studies
A Diamond, JS Sekhon
Review of Economics and Statistics 95 (3), 932-945, 2013
Referral to an extracorporeal membrane oxygenation center and mortality among patients with severe 2009 influenza A (H1N1)
MA Noah, GJ Peek, SJ Finney, MJ Griffiths, DA Harrison, R Grieve, ...
Jama 306 (15), 1659-1668, 2011
Elections and the regression discontinuity design: Lessons from close US house races, 1942–2008
D Caughey, JS Sekhon
Political Analysis 19 (4), 385-408, 2011
Metalearners for estimating heterogeneous treatment effects using machine learning
SR Künzel, JS Sekhon, PJ Bickel, B Yu
Proceedings of the national academy of sciences 116 (10), 4156-4165, 2019
Opiates for the matches: Matching methods for causal inference
JS Sekhon
Annual Review of Political Science 12 (1), 487-508, 2009
Genetic optimization using derivatives: the rgenoud package for R
WR Mebane Jr, JS Sekhon
Journal of Statistical Software 42, 1-26, 2011
The butterfly did it: The aberrant vote for Buchanan in Palm Beach County, Florida
JN Wand, KW Shotts, JS Sekhon, WR Mebane, MC Herron, HE Brady
American Political Science Review 95 (4), 793-810, 2001
When natural experiments are neither natural nor experiments
JS Sekhon, R Titiunik
American Political Science Review 106 (1), 35-57, 2012
The Neyman—Rubin Model of Causal Inference and Estimation Via Matching Methods
J Sekhon
Endogeneity in probit response models
DA Freedman, JS Sekhon
Political Analysis 18 (2), 138-150, 2010
Genetic optimization using derivatives
JS Sekhon, WR Mebane
Political Analysis 7, 187-210, 1998
Estimating causal effects: considering three alternatives to difference-in-differences estimation
S O’Neill, N Kreif, R Grieve, M Sutton, JS Sekhon
Health Services and Outcomes Research Methodology 16 (1), 1-21, 2016
Quality meets quantity: Case studies, conditional probability, and counterfactuals
JS Sekhon
Perspectives on Politics 2 (2), 281-293, 2004
Adjusting treatment effect estimates by post‐stratification in randomized experiments
LW Miratrix, JS Sekhon, B Yu
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2013
Cemented, cementless, and hybrid prostheses for total hip replacement: cost effectiveness analysis
M Pennington, R Grieve, JS Sekhon, P Gregg, N Black, ...
Bmj 346, 2013
Lasso adjustments of treatment effect estimates in randomized experiments
A Bloniarz, H Liu, CH Zhang, JS Sekhon, B Yu
Proceedings of the National Academy of Sciences 113 (27), 7383-7390, 2016
From sample average treatment effect to population average treatment effect on the treated: combining experimental with observational studies to estimate population treatment …
E Hartman, R Grieve, R Ramsahai, JS Sekhon
Journal of the Royal Statistical Society: Series A (Statistics in Society …, 2015
Time-uniform, nonparametric, nonasymptotic confidence sequences
SR Howard, A Ramdas, J McAuliffe, J Sekhon
The Annals of Statistics 49 (2), 1055-1080, 2021
Black candidates and black voters: Assessing the impact of candidate race on uncounted vote rates
MC Herron, JS Sekhon
The Journal of Politics 67 (1), 154-177, 2005
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