laylaparast/SBdecomp: Estimation of the Proportion of SB Explained by Confounders
Uses parametric and nonparametric methods to quantify the proportion of the estimated selection bias (SB) explained by each observed confounder when estimating propensity score weighted treatment effects. Parast, L and Griffin, BA (2020). "Quantifying the Bias due to Observed Individual Confounders in Causal Treatment Effect Estimates". Statistics in Medicine, 39(18): 2447- 2476 <doi: 10.1002/sim.8549>.
Getting started
Browse package contents
Package details |
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| Author | Layla Parast |
| Maintainer | Layla Parast <parast@austin.utexas.edu> |
| License | GPL |
| Version | 1.2 |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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