Revision fe07bfa906d7e155439160caee538a3449cd3877 authored by Dominique Makowski on 08 April 2019, 08:42:41 UTC, committed by cran-robot on 08 April 2019, 08:42:41 UTC
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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/rope_range.R
\title{Find Default Equivalence (ROPE) Region Bounds}
\item{x}{Vector representing a posterior distribution. Can also be a \code{stanreg} or \code{brmsfit} model.}
This function attempts at automatically finding suitable "default"
  values for the Region Of Practical Equivalence (ROPE). Kruschke (2018) suggests
  that such null value could be set, by default, to a range from \code{-0.1} to
  \code{0.1} of a standardized parameter (negligible effect size
  according to Cohen, 1988), which can be generalised for linear models
  to \ifelse{html}{\out{-0.1 * SD<sub>y</sub>, 0.1 * SD<sub>y</sub>}}{\eqn{[-0.1*SD_{y}, 0.1*SD_{y}]}}.
  \cr \cr
  For logistic models, the parameters expressed in log odds ratio can be
  converted to standardized difference through the formula
  \ifelse{html}{\out{sqrt(3)/pi}}{\eqn{\sqrt{3}/\pi}}, resulting in a range
  of \code{-0.055} to \code{-0.055}.
  \cr \cr
  For other models with binary outcome, it is strongly recommended to
  manually specify the rope argument. Currently, the same default is applied
  that for logistic models.
  \cr \cr
  For all other models, \code{-0.1, 0.1} is used to determine the ROPE limits.
model <- rstanarm::stan_glm(vs ~ mpg, data = mtcars, family = "binomial")

model <- brms::brm(mpg ~ wt + cyl, data = mtcars)

Kruschke, J. K. (2018). Rejecting or accepting parameter values in Bayesian estimation. Advances in Methods and Practices in Psychological Science, 1(2), 270-280. \doi{10.1177/2515245918771304}.
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