% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/interpret_bf.R
\name{interpret_bf}
\alias{interpret_bf}
\title{Interpret Bayes Factor (BF)}
\usage{
interpret_bf(
  bf,
  rules = "jeffreys1961",
  include_value = FALSE,
  protect_ratio = TRUE,
  exact = TRUE
)
}
\arguments{
\item{bf}{Value or vector of Bayes factor (BF) values.}

\item{rules}{Can be \code{"jeffreys1961"} (default), \code{"raftery1995"} or custom set
of \code{\link[=rules]{rules()}} (for the \emph{absolute magnitude} of evidence).}

\item{include_value}{Include the value in the output.}

\item{protect_ratio}{Should values smaller than 1 be represented as ratios?}

\item{exact}{Should very large or very small values be reported with a
scientific format (e.g., 4.24e5), or as truncated values (as "> 1000" and
"< 1/1000").}
}
\description{
Interpret Bayes Factor (BF)
}
\details{
Argument names can be partially matched.
}
\section{Rules}{


Rules apply to BF as ratios, so BF of 10 is as extreme as a BF of 0.1 (1/10).
\itemize{
\item Jeffreys (1961) (\code{"jeffreys1961"}; default)
\itemize{
\item \strong{BF = 1} - No evidence
\item \strong{1 < BF <= 3} - Anecdotal
\item \strong{3 < BF <= 10} - Moderate
\item \strong{10 < BF <= 30} - Strong
\item \strong{30 < BF <= 100} - Very strong
\item \strong{BF > 100} - Extreme.
}
\item Raftery (1995) (\code{"raftery1995"})
\itemize{
\item \strong{BF = 1} - No evidence
\item \strong{1 < BF <= 3} - Weak
\item \strong{3 < BF <= 20} - Positive
\item \strong{20 < BF <= 150} - Strong
\item \strong{BF > 150} - Very strong
}
}
}

\examples{
interpret_bf(1)
interpret_bf(c(5, 2))
}
\references{
\itemize{
\item Jeffreys, H. (1961), Theory of Probability, 3rd ed., Oxford University Press, Oxford.
\item Raftery, A. E. (1995). Bayesian model selection in social research. Sociological methodology, 25, 111-164.
\item Jarosz, A. F., & Wiley, J. (2014). What are the odds? A practical guide to computing and reporting Bayes factors. The Journal of Problem Solving, 7(1), 2.
}
}
