bain_sensitivity: Sensitivity analysis for bain

In bain: Bayes Factors for Informative Hypotheses

Sensitivity analysis for bain

Description

Conducts a sensitivity analysis for bain.

Usage

bain_sensitivity(x, hypothesis, fractions = 1, ...)

Arguments

x	An R object containing the outcome of a statistical analysis. Currently, the following objects can be processed: lm(), t_test(), lavaan objects created with the sem(), cfa(), and growth() functions, and named vector objects. See the vignette for elaborations.
hypothesis	A character string containing the informative hypotheses to evaluate. See the vignette for elaborations.
fractions	A number representing the fraction of information in the data used to construct the prior distribution. The default value 1 denotes the minimal fraction, 2 denotes twice the minimal fraction, etc. See the vignette for elaborations.
...	Additional arguments passed to bain.

Details

The Bayes factor for equality constraints is sensitive to a scaling factor applied to the prior distribution. The argument fraction adjusts this scaling factor. The function bain_sensitivity is a wrapper for bain, which accepts a vector for the fractions argument, and returns a list of bain results objects. A table with a sensitivity analysis for specific statistics can be obtained using the summary() function, which accepts the argument summary(which_stat = ...). The available statistics are elements of the $fit table (Fit_eq, Com_eq, Fit_in, Com_in, Fit, Com, BF, PMPa, and PMPb), and elements of the BFmatrix, which can be accessed by matrix notation, e.g.: summary(bain_sens, which_stat = "BFmatrix[1,2]").

Value

A data.frame of class "bain_sensitivity".

Examples

sesamesim$site <- as.factor(sesamesim$site)
res <- lm(sesamesim$postnumb~sesamesim$site-1)
set.seed(4583)
bain_sens <- bain_sensitivity(res, "site1=site2;
                                    site2>site5",
                                    fractions = c(1,2,3))
summary(bain_sens, which_stat = "BF.c")
summary(bain_sens, which_stat = "BFmatrix[1,2]")

bain documentation built on Sept. 27, 2023, 5:06 p.m.