bar.sbdecomp: Creates a Bar Plot

In laylaparast/SBdecomp: Estimation of the Proportion of SB Explained by Confounders

Description

This function creates a bar plot to illustrate the estimated proportion of the observed selection bias explained by each observed confounder used in the propensity score model.

Usage

bar.sbdecomp(output.list, main)

Arguments

output.list	List outputed from main sbdecomp function
main	Title for plot, optional

Value

A bar plot showing the estimated proportions of the estimated selection bias explained by the observed confounders used in the propensity score model is created.

Author(s)

Layla Parast

References

Parast, L and Griffin, BA (2020). "Quantifying the Bias due to Observed Individual Confounders in Causal Treatment Effect Estimates." Statistics in Medicine, In press.

Examples

data(petsdata)
output = sbdecomp(outcome = petsdata$genhealth, treatment = petsdata$gotdog, confounders = 
as.data.frame(petsdata[,c(2:13)]), type = "inclusion", estimation = "parametric",
balance = FALSE) 

bar.sbdecomp(output)

laylaparast/SBdecomp documentation built on Nov. 20, 2021, 7:41 a.m.