corr_ci: Confidence interval for correlation coefficient
Description
Computes the half-width confidence interval for correlation coefficient using
the nonparametric method proposed by Olivoto et al. (2018).
The half-width confidence interval is computed according to the following
equation:
CI_w = 0.45304^r 2.25152 n^-0.50089
where n is the sample size and r is the correlation coefficient.
Usage
corr_ci(
.data = NA,
...,
r = NULL,
n = NULL,
by = NULL,
sel.var = NULL,
verbose = TRUE
)
Value
A tibble containing the values of the correlation, confidence
interval, upper and lower limits for all combination of variables.
Arguments
.data
The data to be analyzed. It can be a data frame (possible with
grouped data passed from dplyr::group_by()) or a symmetric correlation
matrix.
...
Variables to compute the confidence interval. If not informed, all
the numeric variables from .data are used.
r
If data is not available, provide the value for correlation
coefficient.
n
The sample size if data is a correlation matrix or if r is
informed.
by
One variable (factor) to compute the function by. It is a shortcut
to dplyr::group_by(). To compute the statistics by more than
one grouping variable use that function.
sel.var
A variable to shows the correlation with. This will omit all
the pairwise correlations that doesn't contain sel.var.
verbose
If verbose = TRUE then some results are shown in the
console.
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.
tools:::Rd_expr_doi("10.2134/agronj2016.04.0196")