2,455
Views
63
CrossRef citations to date
0
Altmetric
Applications and Case Studies

Uncertainty in Propensity Score Estimation: Bayesian Methods for Variable Selection and Model-Averaged Causal Effects

Pages 95-107 | Received 01 Oct 2012, Published online: 19 Mar 2014

Keep up to date with the latest research on this topic with citation updates for this article.

Read on this site (9)

Alberto Caron, Gianluca Baio & Ioanna Manolopoulou. (2022) Shrinkage Bayesian Causal Forests for Heterogeneous Treatment Effects Estimation. Journal of Computational and Graphical Statistics 31:4, pages 1202-1214.
Read now
Junjing Lin & Jianchang Lin. (2022) Incorporating propensity scores for evidence synthesis under bayesian framework: review and recommendations for clinical studies. Journal of Biopharmaceutical Statistics 32:1, pages 53-74.
Read now
Rana Jreich & Bernard Sebastien. (2021) Comparison of statistical methodologies used to estimate the treatment effect on time-to-event outcomes in observational studies. Journal of Biopharmaceutical Statistics 31:4, pages 469-489.
Read now
David Kaplan & Sinan Yavuz. (2020) An Approach to Addressing Multiple Imputation Model Uncertainty Using Bayesian Model Averaging. Multivariate Behavioral Research 55:4, pages 553-567.
Read now
Pierre Baldi & Babak Shahbaba. (2020) Bayesian Causality. The American Statistician 74:3, pages 249-257.
Read now
Laura H. Gunn, Henryk Gzyl, Enrique ter Horst, Miller Janny Ariza & German Molina. (2019) Maximum entropy in the mean methods in propensity score matching for interval and noisy data. Communications in Statistics - Theory and Methods 48:18, pages 4581-4597.
Read now
Tingting Zhou, Michael R. Elliott & Roderick J. A. Little. (2019) Penalized Spline of Propensity Methods for Treatment Comparison: Rejoinder. Journal of the American Statistical Association 114:525, pages 35-38.
Read now
Corwin Matthew Zigler. (2016) The Central Role of Bayes’ Theorem for Joint Estimation of Causal Effects and Propensity Scores. The American Statistician 70:1, pages 47-54.
Read now
Xun Lu. (2015) A Covariate Selection Criterion for Estimation of Treatment Effects. Journal of Business & Economic Statistics 33:4, pages 506-522.
Read now

Articles from other publishers (54)

Li Li, Pengfei Shi, Qingliang Fan & Wei Zhong. (2024) Causal effect estimation with censored outcome and covariate selection. Statistics & Probability Letters 204, pages 109933.
Crossref
Tathagata Basu, Matthias C. M. Troffaes & Jochen Einbeck. 2024. Symbolic and Quantitative Approaches to Reasoning with Uncertainty. Symbolic and Quantitative Approaches to Reasoning with Uncertainty 359 371 .
Oluwagbenga David Agboola & Han Yu. (2023) Neighborhood-based cross fitting approach to treatment effects with high-dimensional data. Computational Statistics & Data Analysis 186, pages 107780.
Crossref
Dingke Tang, Dehan Kong, Wenliang Pan & Linbo Wang. (2022) Ultra‐high dimensional variable selection for doubly robust causal inference. Biometrics 79:2, pages 903-914.
Crossref
Fan Li, Peng Ding & Fabrizia Mealli. (2023) Bayesian causal inference: a critical review. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 381:2247.
Crossref
Chanmin Kim, Mauricio Tec & Corwin Zigler. (2023) Bayesian nonparametric adjustment of confounding. Biometrics.
Crossref
Yang Liu & Robert J. B. Goudie. (2023) Generalized Geographically Weighted Regression Model within a Modularized Bayesian Framework. Bayesian Analysis -1:-1.
Crossref
Zhixuan Chu & Sheng Li. 2023. Machine Learning for Causal Inference. Machine Learning for Causal Inference 79 100 .
Antonio R. Linero & Joseph L. Antonelli. (2022) The how and why of Bayesian nonparametric causal inference. WIREs Computational Statistics 15:1.
Crossref
Qian Gao, Yu Zhang, Hongwei Sun & Tong Wang. (2022) Evaluation of propensity score methods for causal inference with high-dimensional covariates. Briefings in Bioinformatics 23:4.
Crossref
Riccardo Lucchetti, Luca Pedini & Claudia Pigini. (2022) No such thing as the perfect match: Bayesian Model Averaging for treatment evaluation. Economic Modelling 107, pages 105729.
Crossref
James P Normington, Eric F Lock, Thomas A Murray & Caroline S Carlin. (2021) Bayesian variable selection in hierarchical difference-in-differences models. Statistical Methods in Medical Research 31:1, pages 169-183.
Crossref
Corwin M Zigler. (2021) Invited Commentary: The Promise and Pitfalls of Causal Inference With Multivariate Environmental Exposures. American Journal of Epidemiology 190:12, pages 2658-2661.
Crossref
Qian Gao, Yu Zhang, Jie Liang, Hongwei Sun & Tong Wang. (2021) High-dimensional generalized propensity score with application to omics data. Briefings in Bioinformatics 22:6.
Crossref
Sarah B Peskoe, David Arterburn, Karen J Coleman, Lisa J Herrinton, Michael J Daniels & Sebastien Haneuse. (2021) Adjusting for selection bias due to missing data in electronic health records-based research. Statistical Methods in Medical Research 30:10, pages 2221-2238.
Crossref
Xin Sun, Ling Li, Yanmei Liu, Wen Wang, Minghong Yao, Jing Tan, Yan Ren, Ke Deng, Yu Ma, Yuning Wang, Jin Chen, Wei Huang, Qing Xia, Youping Li & Hongcai Shang. (2021) Assessing Clinical Effects of Traditional Chinese Medicine Interventions: Moving Beyond Randomized Controlled Trials. Frontiers in Pharmacology 12.
Crossref
Tingting Zhou, Michael R. Elliott & Roderick J. A. Little. (2021) Robust Causal Estimation from Observational Studies Using Penalized Spline of Propensity Score for Treatment Comparison. Stats 4:2, pages 529-549.
Crossref
Patrick M. Schnell & Georgia Papadogeorgou. (2020) Mitigating unobserved spatial confounding when estimating the effect of supermarket access on cardiovascular disease deaths. The Annals of Applied Statistics 14:4.
Crossref
Kolyan Ray & Aad van der Vaart. (2020) Semiparametric Bayesian causal inference. The Annals of Statistics 48:5.
Crossref
Joshua L Warren, Wenjing Kong, Thomas J Luben & Howard H Chang. (2020) Critical window variable selection: estimating the impact of air pollution on very preterm birth. Biostatistics 21:4, pages 790-806.
Crossref
P. Richard Hahn, Jared S. Murray & Carlos M. Carvalho. (2020) Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects (with Discussion). Bayesian Analysis 15:3.
Crossref
Kuan Liu, Olli Saarela, Brian M Feldman & Eleanor Pullenayegum. (2020) Estimation of causal effects with repeatedly measured outcomes in a Bayesian framework. Statistical Methods in Medical Research 29:9, pages 2507-2519.
Crossref
Brandon Koch, David M Vock, Julian Wolfson & Laura Boehm Vock. (2020) Variable selection and estimation in causal inference using Bayesian spike and slab priors. Statistical Methods in Medical Research 29:9, pages 2445-2469.
Crossref
Lingyu Li & Eric T. Donnell. (2020) Incorporating Bayesian methods into the propensity score matching framework: A no-treatment effect safety analysis. Accident Analysis & Prevention 145, pages 105691.
Crossref
Shirley X. Liao & Corwin M. Zigler. (2020) Uncertainty in the design stage of two‐stage Bayesian propensity score analysis. Statistics in Medicine 39:17, pages 2265-2290.
Crossref
Michelle Y. Chen, Yan Liu & Bruno D. Zumbo. (2019) A Propensity Score Method for Investigating Differential Item Functioning in Performance Assessment. Educational and Psychological Measurement 80:3, pages 476-498.
Crossref
Yan Liu, Chanmin Kim, Amery D. Wu, Paul Gustafson, Edward Kroc & Bruno D. Zumbo. (2020) Investigating the Performance of Propensity Score Approaches for Differential Item Functioning Analysis. Journal of Modern Applied Statistical Methods 18:1, pages 2-26.
Crossref
Marco Carone, Francesca Dominici & Lianne Sheppard. (2020) In Pursuit of Evidence in Air Pollution Epidemiology: The Role of Causally Driven Data Science. Epidemiology 31:1, pages 1-6.
Crossref
Joseph Antonelli, Giovanni Parmigiani & Francesca Dominici. (2019) High-Dimensional Confounding Adjustment Using Continuous Spike and Slab Priors. Bayesian Analysis 14:3.
Crossref
Christine Choirat, Danielle Braun & Marianthi-Anna Kioumourtzoglou. (2019) Data Science in Environmental Health Research. Current Epidemiology Reports 6:3, pages 291-299.
Crossref
Janine Witte & Vanessa Didelez. (2018) Covariate selection strategies for causal inference: Classification and comparison. Biometrical Journal 61:5, pages 1270-1289.
Crossref
Christopher R King, Krisztina E Escallier, Yo-El S Ju, Nan Lin, Ben Julian Palanca, Sherry Lynn McKinnon & Michael Simon Avidan. (2019) Obstructive sleep apnoea, positive airway pressure treatment and postoperative delirium: protocol for a retrospective observational study. BMJ Open 9:8, pages e026649.
Crossref
Denis Talbot & Victoria Kubuta Massamba. (2019) A descriptive review of variable selection methods in four epidemiologic journals: there is still room for improvement. European Journal of Epidemiology 34:8, pages 725-730.
Crossref
Jongeun Rhee, Francesca Dominici, Antonella Zanobetti, Joel Schwartz, Yun Wang, Qian Di, John Balmes & David C. Christiani. (2019) Impact of Long-Term Exposures to Ambient PM2.5 and Ozone on ARDS Risk for Older Adults in the United States. Chest 156:1, pages 71-79.
Crossref
Adam Slez. (2017) The Difference Between Instability and Uncertainty: Comment on Young and Holsteen (2017). Sociological Methods & Research 48:2, pages 400-430.
Crossref
Susan M Shortreed, Andrea J Cook, R Yates Coley, Jennifer F Bobb & Jennifer C Nelson. (2019) Challenges and Opportunities for Using Big Health Care Data to Advance Medical Science and Public Health. American Journal of Epidemiology 188:5, pages 851-861.
Crossref
Luke Bornn, Neil Shephard & Reza Solgi. (2019) Moment conditions and Bayesian non-parametrics. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 81:1, pages 5-43.
Crossref
Joseph Antonelli, Matthew CefaluNathan PalmerDenis Agniel. (2018) Doubly robust matching estimators for high dimensional confounding adjustment. Biometrics 74:4, pages 1171-1179.
Crossref
Dandan XuMichael J. Daniels & Almut G. Winterstein. (2018) A Bayesian nonparametric approach to causal inference on quantiles. Biometrics 74:3, pages 986-996.
Crossref
Ander Wilson, Corwin M. Zigler, Chirag J. PatelFrancesca Dominici. (2018) Model-averaged confounder adjustment for estimating multivariate exposure effects with linear regression. Biometrics 74:3, pages 1034-1044.
Crossref
Jacob V. Spertus & Sharon-Lise T. Normand. (2018) Bayesian propensity scores for high-dimensional causal inference: A comparison of drug-eluting to bare-metal coronary stents. Biometrical Journal 60:4, pages 721-733.
Crossref
P. Richard Hahn, Carlos M. Carvalho, David Puelz & Jingyu He. (2018) Regularization and Confounding in Linear Regression for Treatment Effect Estimation. Bayesian Analysis 13:1.
Crossref
David FletcherDavid Fletcher. 2018. Model Averaging. Model Averaging 31 55 .
Susan M. ShortreedAshkan Ertefaie. (2017) Outcome‐adaptive lasso: Variable selection for causal inference. Biometrics 73:4, pages 1111-1122.
Crossref
Matthew Cefalu, Francesca Dominici, Nils Arvold & Giovanni Parmigiani. (2017) Model averaged double robust estimation. Biometrics 73:2, pages 410-421.
Crossref
Emma Persson, Jenny Häggström, Ingeborg Waernbaum & Xavier de Luna. (2017) Data-driven algorithms for dimension reduction in causal inference. Computational Statistics & Data Analysis 105, pages 280-292.
Crossref
O. Saarela, L. R. Belzile & D. A. Stephens. (2016) A Bayesian view of doubly robust causal inference: Table 1.. Biometrika 103:3, pages 667-681.
Crossref
Sven Van Poucke, Michiel Thomeer, John Heath & Milan Vukicevic. (2016) Are Randomized Controlled Trials the (G)old Standard? From Clinical Intelligence to Prescriptive Analytics. Journal of Medical Internet Research 18:7, pages e185.
Crossref
Anning Hu & Sarah A Mustillo. (2015) Recent development of propensity score methods in observational studies: Multi-categorical treatment, causal mediation, and heterogeneity. Current Sociology 64:1, pages 60-82.
Crossref
Lauren Hund, Edward J. Bedrick, Curtis Miller, Gabriel Huerta, Teddy Nez, Sandy Ramone, Chris Shuey, Miranda Cajero & Johnnye Lewis. (2015) A Bayesian Framework for Estimating Disease Risk Due to Exposure to Uranium Mine and Mill Waste on the Navajo Nation. Journal of the Royal Statistical Society Series A: Statistics in Society 178:4, pages 1069-1091.
Crossref
Jessica M. Franklin, Wesley Eddings, Robert J. Glynn & Sebastian Schneeweiss. (2015) Regularized Regression Versus the High-Dimensional Propensity Score for Confounding Adjustment in Secondary Database Analyses. American Journal of Epidemiology 182:7, pages 651-659.
Crossref
Chi WangFrancesca DominiciGiovanni ParmigianiCorwin Matthew Zigler. (2015) Accounting for uncertainty in confounder and effect modifier selection when estimating average causal effects in generalized linear models. Biometrics 71:3, pages 654-665.
Crossref
Yucan Wang, Yifei Li & Qinjian Yuan. (2022) Visualization Analysis on the Hotspots and Frontier Evolution of International Big Data Research. Journal of Engineering Studies 06:03, pages 282-293.
Crossref
P. Richard Hahn, Jared S. Murray & Carlos M. Carvalho. (2017) Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects. SSRN Electronic Journal.
Crossref

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.