R: Function to compute Bayes factors for general designs

generalTestBF {BayesFactor} | R Documentation

## Function to compute Bayes factors for general designs

### Description

This function computes Bayes factors corresponding to restrictions on a full model.

### Usage

    generalTestBF(formula, data, whichRandom = NULL, whichModels = "withmain",
      neverExclude = NULL, iterations = 10000,
      progress = getOption("BFprogress", interactive()), rscaleFixed = "medium",
      rscaleRandom = "nuisance", rscaleCont = "medium", rscaleEffects = NULL,
      multicore = FALSE, method = "auto", noSample = FALSE,
      callback = function(...) as.integer(0))

### Arguments

`formula` | a formula containing the full model for the analysis (see Examples)
`data` | a data frame containing data for all factors in the formula
`whichRandom` | a character vector specifying which factors are random
`whichModels` | which set of models to compare; see Details
`neverExclude` | a character vector containing a regular expression (see help for regex for details) that indicates which terms to always keep in the analysis
`iterations` | How many Monte Carlo simulations to generate, if relevant
`progress` | if `TRUE`, show progress with a text progress bar
`rscaleFixed` | prior scale for standardized, reduced fixed effects. A number of preset values can be given as strings; see Details.
`rscaleRandom` | prior scale for standardized random effects
`rscaleCont` | prior scale for standardized slopes
`rscaleEffects` | A named vector of prior settings for individual factors, overriding rscaleFixed and rscaleRandom. Values are scales, names are factor names.
`multicore` | if `TRUE` use multiple cores through the `doMC` package. Unavailable on Windows.
`method` | approximation method, if needed. See `nWayAOV` for details.
`noSample` | if `TRUE`, do not sample, instead returning NA.
`callback` | callback function for third-party interfaces

### Details

See the help for `anovaBF` and `anovaBF` or details.

Models, priors, and methods of computation are provided in Rouder et al. (2012) and Liang et al (2008).

### Value

An object of class `BFBayesFactor`, containing the computed model comparisons

### Note

The function `generalTestBF` can compute Bayes factors for all restrictions of a full model against the null hypothesis that all effects are 0. The total number of tests computed – if all tests are requested – will be 2^K - 1 for K factors or covariates. This number increases very quickly with the number of tested predictors. An option is included to prevent testing too many models: `options('BFMaxModels')`, which defaults to 50,000, is the maximum number of models that will be analyzed at once. This can be increased by increased using `options`.

It is possible to reduce the number of models tested by only testing the most complex model and every restriction that can be formed by removing one factor or interaction using the `whichModels` argument. See the help for `anovaBF` for details.

### Author(s)

Richard D. Morey (richarddmorey@gmail.com)

### References

Rouder, J. N., Morey, R. D., Speckman, P. L., Province, J. M., (2012) Default Bayes Factors for ANOVA Designs. Journal of Mathematical Psychology. 56. p. 356-374.

Liang, F. and Paulo, R. and Molina, G. and Clyde, M. A. and Berger, J. O. (2008). Mixtures of g-priors for Bayesian Variable Selection. Journal of the American Statistical Association, 103, pp. 410-423

### See Also

`lmBF`, for testing specific models, and `regressionBF` and `anovaBF` for other functions for testing multiple models simultaneously.

### Examples

    ## Puzzles example: see ?puzzles and ?anovaBF
    data(puzzles)
    ## neverExclude argument makes sure that participant factor ID
    ## is in all models
    result = generalTestBF(RT ~ shape*color + ID, data = puzzles, whichRandom = "ID",
    neverExclude="ID", progress=FALSE)
    result

[Package BayesFactor version 0.9.12-4.2 Index]