R/corr_ss.R
corr_ss.Rd
Find the required (sufficient) sample size for computing a Pearson correlation coefficient with a desired confidence interval (Olivoto et al., 2018) as follows \[n = {\left[ {\frac{{C{I_w}}}{{{{0.45304}^r} \times 2.25152}}} \right]^{{\rm{ - 0}}{\rm{.50089}}}}\]
where \(CI_w\) is desired confidence interval and \(r\) is the correlation coefficient.
corr_ss(r, CI, verbose = TRUE)
r | The magnitude of the correlation coefficient. |
---|---|
CI | The half-width for confidence interval at p < 0.05. |
verbose | Logical argument. If |
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
Tiago Olivoto tiagoolivoto@gmail.com
# \donttest{ corr_ss(r = 0.60, CI = 0.1)#> ------------------------------------------------- #> Sample size planning for correlation coefficient #> ------------------------------------------------- #> Level of significance: 5% #> Correlation coefficient: 0.6 #> 95% half-width CI: 0.1 #> Required sample size: 194 #> -------------------------------------------------# }