% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/input-priors.R
\name{publication_bias_prior_specification}
\alias{publication_bias_prior_specification}
\alias{bias_prior_specification}
\title{Publication-bias prior specification}
\arguments{
\item{prior_bias}{prior distribution for publication-bias adjustment. For
\code{\link{bselmodel}}, this is usually a weightfunction prior created by
\code{\link{prior_weightfunction}}. For \code{\link{bPET}}, use
\code{\link{prior_PET}}. For \code{\link{bPEESE}}, use
\code{\link{prior_PEESE}}. For \code{\link{RoBMA}}, this can be a single
publication-bias prior distribution or a list of publication-bias prior
distributions. In the single-model bias-adjustment constructors, omitted or
\code{NULL} uses the corresponding default prior distribution.}

\item{prior_bias_null}{prior distribution(s) for null publication-bias
component(s) in \code{\link{RoBMA}}, usually \code{\link{prior_none}()}.
A single prior distribution object creates one null component, a list creates
multiple null components, and \code{NULL} or \code{FALSE} omits the null
publication-bias component.}

\item{model_type}{character string specifying predefined publication-bias
model ensembles for \code{\link{RoBMA}}. One of \code{"PSMA"},
\code{"6w"}, \code{"2w"}, or \code{"PP"}.}

\item{steps}{numeric vector of one-sided p-value cut points for the default
\code{\link{bselmodel}} weightfunction prior. If \code{prior_bias} is supplied,
the prior distribution carries its own p-value cut points.}
}
\description{
Publication-bias prior distributions are specified separately from the
meta-analytic prior distributions documented in
\code{\link{prior_specification}}. They define selection-model weights,
PET/PEESE regression coefficients, or the publication-bias model space in
\code{\link{RoBMA}}.
}
\details{
\subsection{Single-model bias-adjustment priors}{

\code{\link{bselmodel}}, \code{\link{bPET}}, and \code{\link{bPEESE}} fit one
publication-bias adjustment at a time. The \code{prior_bias} argument must
match the fitted bias-adjustment type.

\tabular{lll}{
Constructor \tab Prior constructor \tab Default prior distribution \cr
\code{bselmodel()} \tab \code{\link{prior_weightfunction}} \tab one-sided cumulative weightfunction with \code{steps = 0.025} \cr
\code{bPET()} \tab \code{\link{prior_PET}} \tab positive Cauchy centered at 0 \cr
\code{bPEESE()} \tab \code{\link{prior_PEESE}} \tab positive Cauchy centered at 0, with UISD-adjusted scale
}

The default PET prior distribution uses
\code{RoBMA.get_option("default_bias_PET.scale")}. The default PEESE prior
distribution uses \code{RoBMA.get_option("default_bias_PEESE.scale")} after
rescaling to the analyzed effect-size measure. The default weightfunction
prior distribution uses \code{RoBMA.get_option("default_bias_weightfunction.alpha")}
for each cumulative-Dirichlet alpha parameter.
}

\subsection{Model-averaged publication-bias priors}{

\code{\link{RoBMA}} averages over publication-bias components. By default,
\code{prior_bias_null} is \code{\link{prior_none}()} and \code{model_type}
determines the alternative components:

\tabular{ll}{
\code{"PSMA"} \tab six weight functions, PET, and PEESE \cr
\code{"6w"} \tab six weight functions \cr
\code{"2w"} \tab two two-sided weight functions \cr
\code{"PP"} \tab PET and PEESE
}

Custom \code{prior_bias} replaces the preset alternative components. If
\code{prior_bias} is omitted, \code{model_type} still supplies the default
alternative components even when \code{prior_bias_null} is customized or
omitted. Setting \code{prior_bias = NULL} or \code{prior_bias = FALSE}
omits all alternative bias-adjustment models. Setting
\code{prior_bias_null = NULL} or \code{prior_bias_null = FALSE} omits the
no-bias component.

Each publication-bias component has a prior model weight. User-specified
components receive equal weights unless their prior objects set
\code{prior_weights}. The \code{"2w"} and \code{"6w"} presets split the
alternative bias mass equally across their weight functions, \code{"PP"}
splits it equally across PET and PEESE, and \code{"PSMA"} assigns half of the
alternative bias mass to the six weight functions combined and one quarter
each to PET and PEESE.

Publication-bias prior distributions are not rescaled by \code{rescale_priors}.
The exception is the default PEESE prior distribution, whose scale is adjusted
to the effect-size measure via the unit-information standard deviation.
}
}
\seealso{
\code{\link{prior_weightfunction}}, \code{\link{prior_PET}},
\code{\link{prior_PEESE}}, \code{\link{prior_none}},
\code{\link{RoBMA_prior_specification}},
\code{\link{prior_specification}}
}
