The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Bayesian Nonparametric Modeling for Causal Inference
Abstract
Researchers have long struggled to identify causal effects in nonexperimental settings. Many recently proposed strategies assume ignorability of the treatment assignment mechanism and require fitting two models—one for the assignment mechanism and one for the response surface. This article proposes a strategy that instead focuses on very flexibly modeling just the response surface using a Bayesian nonparametric modeling procedure, Bayesian Additive Regression Trees (BART). BART has several advantages: it is far simpler to use than many recent competitors, requires less guesswork in model fitting, handles a large number of predictors, yields coherent uncertainty intervals, and fluidly handles continuous treatment variables and missing data for the outcome variable. BART also naturally identifies heterogeneous treatment effects. BART produces more accurate estimates of average treatment effects compared to propensity score matching, propensity-weighted estimators, and regression adjustment in the nonlinear simulation situations examined. Further, it is highly competitive in linear settings with the “correct” model, linear regression. Supplemental materials including code and data to replicate simulations and examples from the article as well as methods for population inference are available online.
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Cites
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“Some methods focus primarily on appropriately controlling for the treatment assignment mechanism such as with subclassification or matching (e.g., Rosenbaum and Rubin 1983; Gu and Rosenbaum 1993; Abadie and Imbens 2006), parametric inverse probability weighting approaches (e.”
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Metadata
- Authors
- Hill, J. L.
- Venue
- Journal of Computational and Graphical Statistics
- Publisher
- Informa UK Limited
- Published
- 2011-01
- Volume
- 20
- Issue
- 1
- Pages
- 217-240
- ISSN
- 1061-8600 (ISSN-L)
- 1537-2715
- OpenAlex
- W2064903582
- Cited by
- 1,139
- References
- 8
- FWCI
- 4.31
- Type
- journal article
- Language
- en
- Open access
- closed
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