konfound_lmer: Konfound Analysis for Linear Mixed-Effects Models

In jrosen48/konfound: Quantify the Robustness of Causal Inferences

Konfound Analysis for Linear Mixed-Effects Models

Description

This function performs konfound analysis on a linear mixed-effects model object produced by lme4::lmer. It calculates the sensitivity of inferences for fixed effects in the model. It supports analysis for a single variable or multiple variables.

Usage

konfound_lmer(
  model_object,
  tested_variable_string,
  test_all,
  alpha,
  tails,
  index,
  to_return
)

Arguments

model_object	The mixed-effects model object produced by lme4::lmer.
tested_variable_string	The name of the fixed effect being tested.
test_all	Boolean indicating whether to test all fixed effects or not.
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 fixed effect(s).

jrosen48/konfound documentation built on Nov. 21, 2024, 4:42 a.m.