Jared Murray
Jared Murray
Assistant Professor of Statistics, University of Texas at Austin
Verified email at mccombs.utexas.edu - Homepage
Cited by
Cited by
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
Bayesian regression tree models for causal inference: regularization, confounding, and heterogeneous effects
PR Hahn, JS Murray, CM Carvalho
Bayesian Gaussian copula factor models for mixed data
JS Murray, DB Dunson, L Carin, JE Lucas
Journal of the American Statistical Association 108 (502), 656-665, 2013
Multiple Imputation: A Review of Practical and Theoretical Findings
JS Murray
Statistical Science 33 (2), 142-159, 2018
Multiple imputation of missing categorical and continuous values via Bayesian mixture models with local dependence
JS Murray, JP Reiter
Journal of the American Statistical Association 111 (516), 1466-1479, 2016
Log-linear Bayesian additive regression trees for multinomial Logistic and count regression models
JS Murray
Journal of the American Statistical Association, 1-35, 2020
Bayesian additive regression trees: A review and look forward
J Hill, A Linero, J Murray
Annual Review of Statistics and Its Application 7, 251-278, 2020
Bart with targeted smoothing: An analysis of patient-specific stillbirth risk
JE Starling, JS Murray, CM Carvalho, RK Bukowski, JG Scott
Annals of Applied Statistics 14 (1), 28-50, 2020
Probabilistic Record Linkage and Deduplication after Indexing, Blocking, and Filtering
JS Murray
Journal of Privacy and Confidentiality 7 (1), 2016
Atlantic Causal Inference Conference (ACIC) Data Analysis Challenge 2017
PR Hahn, V Dorie, JS Murray
arXiv preprint arXiv:1905.09515, 2019
Assessing treatment effect variation in observational studies: Results from a data challenge
C Carvalho, A Feller, J Murray, S Woody, D Yeager
Observational Studies 5 (2), 21-35, 2019
Scaling Bayesian Probabilistic Record Linkage with Post-Hoc Blocking: An Application to the California Great Registers
BS McVeigh, BT Spahn, JS Murray
arXiv preprint arXiv:1905.05337, 2019
Model interpretation through lower-dimensional posterior summarization
S Woody, CM Carvalho, JS Murray
Journal of Computational and Graphical Statistics, 1-9, 2020
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
Bayesian learning of joint distributions of objects
A Banerjee, J Murray, D Dunson
Artificial Intelligence and Statistics, 1-9, 2013
Targeted Smooth Bayesian Causal Forests: An analysis of heterogeneous treatment effects for simultaneous vs. interval medical abortion regimens over gestation
JE Starling, JS Murray, PA Lohr, ARA Aiken, CM Carvalho, JG Scott
The Annals of Applied Statistics 15 (3), 1194-1219, 2021
Patient Clustering with Uncoded Text in Electronic Medical Records
R Henao, J Murray, G Ginsburg, L Carin, JE Lucas
AMIA Annual Symposium Proceedings 2013, 592, 2013
Teacher mindsets help explain where a growth mindset intervention does and doesn’t work
DS Yeager, JM Carroll, J Buontempo, A Cimpian, S Woody, R Crosnoe, ...
Manuscript in preparation, 2020
Estimating heterogeneous effects of continuous exposures using Bayesian tree ensembles: revisiting the impact of abortion rates on crime
S Woody, CM Carvalho, PR Hahn, JS Murray
arXiv preprint arXiv:2007.09845, 2020
Stochastic tree ensembles for regularized supervised learning
J He, S Yalov, J Murray, PR Hahn
Technical report, 2019
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