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Sample size planning for a desired Pearson's correlation confidence interval

Source: R/corr_ss.R
corr_ss.Rd

[Stable]

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.

Usage

corr_ss(r, CI, verbose = TRUE)

Arguments

r

The magnitude of the correlation coefficient.

CI

The half-width for confidence interval at p < 0.05.

verbose

Logical argument. If verbose = FALSE the code is run silently.

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

Author

Tiago Olivoto tiagoolivoto@gmail.com

Examples


# \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
#> ------------------------------------------------- 
# }