mbias: Sensitivity analysis to correct for selection bias caused by...

In episensr: Basic Sensitivity Analysis of Epidemiological Results

Sensitivity analysis to correct for selection bias caused by M bias.

Description

Simple sensitivity analysis to correct for selection bias caused by M bias using estimates of the odds ratios relating the variables.

Usage

mbias(or, var = c("y", "x", "a", "b", "m"))

Arguments

or	Vector defining the input bias parameters, in the following order: Odds ratio between A and the exposure E, Odds ratio between A and the collider M, Odds ratio between B and the collider M, Odds ratio between B and the outcome D, Odds ratio observed between the exposure E and the outcome D.
var	Vector defining variable names, in the following order: Outcome, Exposure, A, B, Collider.

Value

A list with elements:

model	Bias analysis performed.
mbias.parms	Three maximum bias parameters: in collider-exposure relationship created by conditioning on the collider, in collider-outcome relationship created by conditioning on the collider, and in exposure-outcome relationship created by conditioning on the collider.
adj.measures	Selection bias corrected odds ratio.
bias.parms	Input bias parameters.
labels	Variables' labels.

References

Greenland S. Quantifying biases in causal models: classical confounding vs. collider-stratification bias. Epidemiology 2003;14:300-6.

Examples

mbias(or = c(2, 5.4, 2.5, 1.5, 1),
var = c("HIV", "Circumcision", "Muslim", "Low CD4", "Participation"))

episensr documentation built on Aug. 30, 2023, 5:09 p.m.