# bain_sensitivity: Sensitivity analysis for bain In bain: Bayes Factors for Informative Hypotheses

 bain_sensitivity R Documentation

## 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.