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 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
Multiple Imputation: A Review of Practical and Theoretical Findings
JS Murray
Statistical Science 33 (2), 142-159, 2018
Log-linear Bayesian additive regression trees for multinomial Logistic and count regression models
JS Murray
Journal of the American Statistical Association, 1-35, 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
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
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
Bayesian learning of joint distributions of objects
A Banerjee, J Murray, D Dunson
Artificial Intelligence and Statistics, 1-9, 2013
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
Targeted Smooth Bayesian Causal Forests: An analysis of heterogeneous treatment effects for simultaneous versus interval medical abortion regimens over gestation
JE Starling, JS Murray, PA Lohr, ARA Aiken, CM Carvalho, JG Scott
arXiv preprint arXiv:1905.09405, 2019
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
Model interpretation through lower-dimensional posterior summarization
S Woody, CM Carvalho, JS Murray
Journal of Computational and Graphical Statistics, 1-9, 2020
Assessing Treatment Effect Variation in Observational Studies: Results from a Data Challenge
C Carvalho, A Feller, J Murray, S Woody, D Yeager
arXiv preprint arXiv:1907.07592, 2019
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
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
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
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