mkonfound: Meta-Analysis and Sensitivity Analysis for Multiple Studies

In jrosen48/konfound: Quantify the Robustness of Causal Inferences

Meta-Analysis and Sensitivity Analysis for Multiple Studies

Description

Performs sensitivity analysis for multiple models, where parameters are stored in a data frame. It calculates the amount of bias required to invalidate or sustain an inference for each case in the data frame.

Usage

mkonfound(d, t, df, alpha = 0.05, tails = 2, return_plot = FALSE)

Arguments

d	A data frame or tibble containing t-statistics and associated degrees of freedom.
t	Column name or vector of t-statistics.
df	Column name or vector of degrees of freedom associated with t-statistics.
alpha	Significance level for hypothesis testing.
tails	Number of tails for the test (1 or 2).
return_plot	Whether to return a plot of the percent bias (default is 'FALSE').

Value

Depending on 'return_plot', either returns a data frame with analysis results or a plot.

Examples

## Not run: 
mkonfound_ex
str(d)
mkonfound(mkonfound_ex, t, df)

## End(Not run)

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