konfound_glm_dichotomous: Konfound Analysis for Generalized Linear Models with...

In konfound: Quantify the Robustness of Causal Inferences

Konfound Analysis for Generalized Linear Models with Dichotomous Outcomes

Description

This function performs konfound analysis on a generalized linear model object with a dichotomous outcome. It uses 'broom' to tidy model outputs and calculates the sensitivity of inferences.

Usage

konfound_glm_dichotomous(
  model_object,
  tested_variable_string,
  alpha,
  tails,
  to_return,
  n_treat,
  switch_trm,
  replace
)

Arguments

model_object	The model object produced by glm.
tested_variable_string	The name of the variable being tested.
alpha	Significance level for hypothesis testing.
tails	Number of tails for the test (1 or 2).
to_return	The type of output to return.
n_treat	Number of treatment cases.
switch_trm	Term to switch for sensitivity analysis.
replace	Boolean indicating whether to replace cases or not.

Value

The results of the konfound analysis.

konfound documentation built on June 8, 2025, 11:10 a.m.