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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/generalTestBF.R
\name{generalTestBF}
\alias{generalTestBF}
\title{Function to compute Bayes factors for general designs}
\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{
\item{formula}{a formula containing the full model for the analysis
(see Examples)}
\item{data}{a data frame containing data for all factors in the formula}
\item{whichRandom}{a character vector specifying which factors are random}
\item{whichModels}{which set of models to compare; see Details}
\item{neverExclude}{a character vector containing a regular expression (see
help for \link{regex} for details) that indicates which terms to always keep
in the analysis}
\item{iterations}{How many Monte Carlo simulations to generate, if relevant}
\item{progress}{if \code{TRUE}, show progress with a text progress bar}
\item{rscaleFixed}{prior scale for standardized, reduced fixed effects. A
number of preset values can be given as strings; see Details.}
\item{rscaleRandom}{prior scale for standardized random effects}
\item{rscaleCont}{prior scale for standardized slopes}
\item{rscaleEffects}{A named vector of prior settings for individual factors,
overriding rscaleFixed and rscaleRandom. Values are scales, names are factor names.}
\item{multicore}{if \code{TRUE} use multiple cores through the \code{doMC}
package. Unavailable on Windows.}
\item{method}{approximation method, if needed. See \code{\link{nWayAOV}} for
details.}
\item{noSample}{if \code{TRUE}, do not sample, instead returning NA.}
\item{callback}{callback function for third-party interfaces}
}
\value{
An object of class \code{BFBayesFactor}, containing the computed
model comparisons
}
\description{
This function computes Bayes factors corresponding to restrictions on a full model.
}
\details{
See the help for \code{\link{anovaBF}} and \code{\link{anovaBF}} or details.
Models, priors, and methods of computation are provided in Rouder et al.
(2012) and Liang et al (2008).
}
\note{
The function \code{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 \eqn{2^K-1}{2^K - 1}
for \eqn{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: \code{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 \code{\link{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 \code{whichModels} argument. See the
help for \code{\link{anovaBF}} for details.
}
\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
}
\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
}
\seealso{
\code{\link{lmBF}}, for testing specific models, and
\code{\link{regressionBF}} and \code{anovaBF} for other functions for
testing multiple models simultaneously.
}
\author{
Richard D. Morey (\email{richarddmorey@gmail.com})
}
\keyword{htest}
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