# R/corr_ss.R In metan: Multi Environment Trials Analysis

#### Documented in corr_ss

#' Sample size planning for a desired Pearson's correlation confidence interval
#' @description
#' r badge('stable')
#'
#' Find the required (sufficient) sample size for computing a Pearson
#' correlation coefficient with a desired confidence interval (Olivoto et al.,
#' 2018) as follows
#'\mjsdeqn{n = {\left[ {\frac{{C{I_w}}}{{{{0.45304}^r} \times 2.25152}}} \right]^{{\rm{ - 0}}{\rm{.50089}}}}}
#'
#' where \mjseqn{CI_w} is desired confidence interval and \mjseqn{r} is the
#' correlation coefficient.
#'
#' @param r The magnitude of the correlation coefficient.
#' @param CI The half-width for confidence interval at p < 0.05.
#' @param verbose Logical argument. If verbose = FALSE the code is run
#'   silently.
#' @author Tiago Olivoto \email{tiagoolivoto@@gmail.com}
#' @references Olivoto, T., A.D.C. Lucio, V.Q. Souza, M. Nardino, M.I. Diel,
#'   B.G. Sari, D.. K. Krysczun, D. Meira, and C. Meier. 2018. Confidence
#'   interval width for Pearson's correlation coefficient: a
#'   Gaussian-independent estimator based on sample size and strength of
#'   association. Agron. J. 110:1-8.
#'   \doi{10.2134/agronj2016.04.0196}
#'
#' @export
#' @examples
#'
#' \donttest{
#' corr_ss(r = 0.60, CI = 0.1)
#' }
#'
#'
corr_ss <- function(r, CI, verbose = TRUE) {
n <- round((CI/(0.45304^r * 2.25152))^(1/-0.50089), 0)
if(verbose == TRUE){
cat("-------------------------------------------------", "\n")
cat("Sample size planning for correlation coefficient", "\n")
cat("-------------------------------------------------", "\n")
cat(paste0("Level of significance: 5%", "\nCorrelation coefficient: ", r, "\n95% half-width CI: ",
CI, "\nRequired sample size: ", n, "\n"))
cat("-------------------------------------------------", "\n")
}
invisible(tibble(Description = c("Significance level (%)", "Correlation", "95% half-width CI", "Sample size"),
Value = c(95, r, CI, n))
)
}


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metan documentation built on March 7, 2023, 5:34 p.m.