View source: R/generalTestBF.R

generalTestBF | R Documentation |

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

```
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)
)
```

`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 |

`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 |

`method` |
approximation method, if needed. See |

`noSample` |
if |

`callback` |
callback function for third-party interfaces |

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).

An object of class `BFBayesFactor`

, containing the computed
model comparisons

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.

Richard D. Morey (richarddmorey@gmail.com)

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

`lmBF`

, for testing specific models, and
`regressionBF`

and `anovaBF`

for other functions for
testing multiple models simultaneously.

```
## 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
```

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