| A national experiment reveals where a growth mindset improves achievement DS Yeager, P Hanselman, GM Walton, JS Murray, R Crosnoe, C Muller, ... Nature 573 (7774), 364-369, 2019 | 236 | 2019 |
| Bayesian regression tree models for causal inference: Regularization, confounding, and heterogeneous effects (with discussion) PR Hahn, JS Murray, CM Carvalho Bayesian Analysis 15 (3), 965-1056, 2020 | 126 | 2020 |
| Decoupling shrinkage and selection in Bayesian linear models: a posterior summary perspective PR Hahn, CM Carvalho Journal of the American Statistical Association 110 (509), 435-448, 2015 | 99 | 2015 |
| A survey of learning causality with data: Problems and methods R Guo, L Cheng, J Li, PR Hahn, H Liu ACM Computing Surveys (CSUR) 53 (4), 1-37, 2020 | 50 | 2020 |
| Regularization and confounding in linear regression for treatment effect estimation PR Hahn, CM Carvalho, D Puelz, J He Bayesian Analysis 13 (1), 163-182, 2018 | 47* | 2018 |
| A sparse factor analytic probit model for congressional voting patterns P Richard Hahn, CM Carvalho, JG Scott Journal of the Royal Statistical Society: Series C (Applied Statistics) 61 …, 2012 | 37 | 2012 |
| Efficient sampling for Gaussian linear regression with arbitrary priors PR Hahn, J He, H Lopes Journal of Computational and Graphical Statistics, 2018 | 28* | 2018 |
| XBART: Accelerated Bayesian additive regression trees J He, S Yalov, PR Hahn The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 27* | 2019 |
| Partial factor modeling: predictor-dependent shrinkage for linear regression PR Hahn, CM Carvalho, S Mukherjee Journal of the American Statistical Association 108 (503), 999-1008, 2013 | 26* | 2013 |
| Variable selection in seemingly unrelated regressions with random predictors D Puelz, PR Hahn, CM Carvalho Bayesian Analysis 12 (4), 969-989, 2017 | 22 | 2017 |
| Atlantic causal inference conference (acic) data analysis challenge 2017 PR Hahn, V Dorie, JS Murray arXiv preprint arXiv:1905.09515, 2019 | 17 | 2019 |
| Prediction versus inducement and the informational efficiency of going concern opinions J Gerakos, PR Hahn, A Kovrijnykh, F Zhou Available at SSRN 2802971, 2016 | 17 | 2016 |
| Bayesian factor model shrinkage for linear IV regression with many instruments PR Hahn, J He, H Lopes Journal of Business & Economic Statistics 36 (2), 278-287, 2018 | 16 | 2018 |
| A Bayesian partial identification approach to inferring the prevalence of accounting misconduct PR Hahn, JS Murray, I Manolopoulou Journal of the American Statistical Association 111 (513), 14-26, 2016 | 14 | 2016 |
| Sparse mean-variance portfolios: A penalized utility approach D Puelz, PR Hahn, CM Carvalho arXiv preprint arXiv:1512.02310, 2015 | 14* | 2015 |
| Where and for whom can a brief, scalable mindset intervention improve adolescents’ educational trajectories DS Yeager, P Hanselman, GM Walton, R Crosnoe, C Muller, E Tipton, ... PsyArXiv Preprints, 2018 | 13 | 2018 |
| On recursive Bayesian predictive distributions PR Hahn, R Martin, SG Walker Journal of the American Statistical Association 113 (523), 1085-1093, 2018 | 12 | 2018 |
| A symmetric prior for multinomial probit models LF Burgette, D Puelz, PR Hahn Bayesian Analysis, 2020 | 11* | 2020 |
| A semiparametric model for assessing cognitive hierarchy theories of beauty contest games PR Hahn, K Lum, C Mela Working paper, Duke University, 2010 | 11 | 2010 |
| Post-processing posteriors over precision matrices to produce sparse graph estimates A Bashir, CM Carvalho, PR Hahn, MB Jones Bayesian Analysis 14 (4), 1075-1090, 2019 | 8 | 2019 |
Carlos M. CarvalhoThe University of Texas at AustinVerified email at mccombs.utexas.edu
