# BFBayesFactor-class: General S4 class for representing multiple Bayes factor model... In BayesFactor: Computation of Bayes Factors for Common Designs

## Description

The `BFBayesFactor` class is a general S4 class for representing models model comparison via Bayes factor.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27``` ```## S4 method for signature 'numeric,BFBayesFactor' e1 / e2 ## S4 method for signature 'BFBayesFactor,BFBayesFactor' e1 / e2 ## S4 method for signature 'BFBayesFactor,index,missing,missing' x[i, j, ..., drop = TRUE] ## S4 method for signature 'BFBayesFactor' t(x) ## S4 method for signature 'BFBayesFactor' which.max(x) ## S4 method for signature 'BFBayesFactor' which.min(x) ## S4 method for signature 'BFBayesFactor' is.na(x) ## S4 method for signature 'BFBayesFactor,BFodds' e1 * e2 ## S4 method for signature 'BFBayesFactorTop,index,missing,missing' x[i, j, ..., drop = TRUE] ```

## Arguments

 `e1` Numerator of the ratio `e2` Denominator of the ratio `x` BFBayesFactor object `i` indices indicating elements to extract `j` unused for BFBayesFactor objects `...` further arguments passed to related methods `drop` unused

## Details

`BFBayesFactor` objects can be inverted by taking the reciprocal and can be divided by one another, provided both objects have the same denominator. In addition, the `t` (transpose) method can be used to invert Bayes factor objects.

The `BFBayesFactor` class has the following slots defined:

numerator

a list of models all inheriting `BFmodel`, each providing a single denominator

denominator

a single `BFmodel` object serving as the denominator for all model comparisons

bayesFactor

a data frame containing information about the comparison between each numerator and the denominator

data

a data frame containing the data used for the comparison

version

character string giving the version and revision number of the package that the model was created in

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```## Compute some Bayes factors to demonstrate division and indexing data(puzzles) bfs <- anovaBF(RT ~ shape*color + ID, data = puzzles, whichRandom = "ID", progress=FALSE) ## First and second models can be separated; they remain BFBayesFactor objects b1 = bfs b2 = bfs b1 ## We can invert them, or divide them to obtain new model comparisons 1/b1 b1 / b2 ## Use transpose to create a BFBayesFactorList t(bfs) ```

### Example output

```Loading required package: coda
************

Type BFManual() to open the manual.
************
Bayes factor analysis
--------------
 shape + ID : 2.853267 <U+00B1>1.72%

Against denominator:
RT ~ ID
---
Bayes factor type: BFlinearModel, JZS

Bayes factor analysis
--------------
 ID : 0.3504755 <U+00B1>1.72%

Against denominator:
RT ~ shape + ID
---
Bayes factor type: BFlinearModel, JZS

Bayes factor analysis
--------------
 shape + ID : 1.012727 <U+00B1>1.99%

Against denominator:
RT ~ color + ID
---
Bayes factor type: BFlinearModel, JZS

denominator
numerator shape + ID color + ID shape + color + ID
ID  0.3504755  0.3549359         0.08450643
denominator
numerator shape + color + shape:color + ID
ID                        0.2342931
```

BayesFactor documentation built on May 2, 2019, 7 a.m.