sf: Calculate sensitivity of treatment effect estimate to...

In causens: Perform Causal Sensitivity Analyses Using Various Statistical Methods

Calculate sensitivity of treatment effect estimate to unmeasured confounding

Description

This function calculates the sensitivity of a treatment effect estimate to unmeasured confounding, as described in Rosenbaum (2002). The sensitivity is defined as the maximum strength of association between the unmeasured confounder and the treatment assignment that would be needed to explain away the observed treatment effect estimate. This function assumes that the treatment assignment is binary and that the outcome is continuous.

Usage

sf(z, e, form = "constant", c1 = 0, c0 = 0, s1 = 0, s0 = 0)

Arguments

z	Treatment assignment (binary: 0 or 1)
e	Propensity score value (numeric)
form	Form of the sensitivity function (character: "constant" or "linear")
c1	Value of the sensitivity function when z = 1 (numeric)
c0	Value of the sensitivity function when z = 0 (numeric)
s1	Slope of the sensitivity function when z = 1 (numeric)
s0	Slope of the sensitivity function when z = 0 (numeric)

Value

Sensitivity of treatment effect estimate to unmeasured confounding (numeric)

sf(z, e, form)

causens documentation built on June 8, 2025, 10:03 a.m.