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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>.
Package details 


Author  Layla Parast 
Maintainer  Layla Parast <parast@austin.utexas.edu> 
License  GPL 
Version  1.2 
Package repository  View on CRAN 
Installation 
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