% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/interpret_r.R
\name{interpret_r}
\alias{interpret_r}
\alias{interpret_phi}
\alias{interpret_cramers_v}
\alias{interpret_rank_biserial}
\alias{interpret_fei}
\title{Interpret Correlation Coefficient}
\usage{
interpret_r(r, rules = "funder2019", ...)

interpret_phi(r, rules = "funder2019", ...)

interpret_cramers_v(r, rules = "funder2019", ...)

interpret_rank_biserial(r, rules = "funder2019", ...)

interpret_fei(r, rules = "funder2019", ...)
}
\arguments{
\item{r}{Value or vector of correlation coefficient.}

\item{rules}{Can be \code{"funder2019"} (default), \code{"gignac2016"}, \code{"cohen1988"},
\code{"evans1996"}, \code{"lovakov2021"} or a custom set of \code{\link[=rules]{rules()}}.}

\item{...}{Not directly used.}
}
\description{
Interpret Correlation Coefficient
}
\details{
Since Cohen's \emph{w} does not have a fixed upper bound, for all by the most
simple of cases (2-by-2 or 1-by-2 tables), interpreting Cohen's \emph{w} as a
correlation coefficient is inappropriate (Ben-Shachar, et al., 2024; Cohen,
1988, p. 222). Please us \code{\link[=cramers_v]{cramers_v()}} of the like instead.
}
\note{
As \eqn{\phi}{\phi} can be larger than 1 - it is recommended to compute
and interpret Cramer's \emph{V} instead.
}
\section{Rules}{


Rules apply to positive and negative \emph{r} alike.
\itemize{
\item Funder & Ozer (2019) (\code{"funder2019"}; default)
\itemize{
\item \strong{r < 0.05} - Tiny
\item \strong{0.05 <= r < 0.1} - Very small
\item \strong{0.1 <= r < 0.2} - Small
\item \strong{0.2 <= r < 0.3} - Medium
\item \strong{0.3 <= r < 0.4} - Large
\item \strong{r >= 0.4} - Very large
}
\item Gignac & Szodorai (2016) (\code{"gignac2016"})
\itemize{
\item \strong{r < 0.1} - Very small
\item \strong{0.1 <= r < 0.2} - Small
\item \strong{0.2 <= r < 0.3} - Moderate
\item \strong{r >= 0.3} - Large
}
\item Cohen (1988) (\code{"cohen1988"})
\itemize{
\item \strong{r < 0.1} - Very small
\item \strong{0.1 <= r < 0.3} - Small
\item \strong{0.3 <= r < 0.5} - Moderate
\item \strong{r >= 0.5} - Large
}
\item Lovakov & Agadullina (2021) (\code{"lovakov2021"})
\itemize{
\item \strong{r < 0.12} - Very small
\item \strong{0.12 <= r < 0.24} - Small
\item \strong{0.24 <= r < 0.41} - Moderate
\item \strong{r >= 0.41} - Large
}
\item Evans (1996) (\code{"evans1996"})
\itemize{
\item \strong{r < 0.2} - Very weak
\item \strong{0.2 <= r < 0.4} - Weak
\item \strong{0.4 <= r < 0.6} - Moderate
\item \strong{0.6 <= r < 0.8} - Strong
\item \strong{r >= 0.8} - Very strong
}
}
}

\examples{
interpret_r(.015)
interpret_r(c(.5, -.02))
interpret_r(.3, rules = "lovakov2021")
}
\references{
\itemize{
\item Lovakov, A., & Agadullina, E. R. (2021). Empirically Derived Guidelines for
Effect Size Interpretation in Social Psychology. European Journal of Social
Psychology.
\item Funder, D. C., & Ozer, D. J. (2019). Evaluating effect size in
psychological research: sense and nonsense. Advances in Methods and Practices
in Psychological Science.
\item Gignac, G. E., & Szodorai, E. T. (2016). Effect size guidelines for
individual differences researchers. Personality and individual differences,
102, 74-78.
\item Cohen, J. (1988). Statistical power analysis for the behavioral sciences
(2nd Ed.). New York: Routledge.
\item Evans, J. D. (1996). Straightforward statistics for the behavioral
sciences. Thomson Brooks/Cole Publishing Co.
\item Ben-Shachar, M.S., Patil, I., Thériault, R., Wiernik, B.M., Lüdecke, D.
(2023). Phi, Fei, Fo, Fum: Effect Sizes for Categorical Data That Use the
Chi‑Squared Statistic. Mathematics, 11, 1982. \doi{10.3390/math11091982}
}
}
\seealso{
Page 88 of APA's 6th Edition.
}
\keyword{interpreters}
