konfound_glm: Konfound Analysis for Generalized Linear Models

In jrosen48/konfound: Quantify the Robustness of Causal Inferences

Konfound Analysis for Generalized Linear Models

Description

This function performs konfound analysis on a generalized linear model object. It uses 'broom' to tidy model outputs and calculates the sensitivity of inferences. It supports analysis for a single variable or multiple variables.

Usage

konfound_glm(
  model_object,
  tested_variable_string,
  alpha,
  tails,
  index = "RIR",
  to_return
)

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).
index	Type of sensitivity analysis ('RIR' by default).
to_return	The type of output to return.

Value

The results of the konfound analysis for the specified variable(s).

jrosen48/konfound documentation built on April 13, 2024, 3:47 a.m.