This function computes the confidence interval for a given correlation and
its sample size. This is useful to obtain confidence intervals for
correlations reported in papers when informing power analyses.

`confIntR(r, N, conf.level = 0.95, plot = FALSE)`

## Arguments

- r
The observed correlation coefficient.

- N
The sample size of the sample where the correlation was computed.

- conf.level
The desired confidence level of the confidence interval.

- plot
Whether to show a plot.

## Value

The confidence interval(s) in a matrix with two columns. The left
column contains the lower bound, the right column the upper bound. The
`rownames()`

are the observed correlations, and the
`colnames()`

are 'lo' and 'hi'. The confidence level and sample
size are stored as attributes. The results are returned like this to make it
easy to access single correlation coefficients from the resulting object
(see the examples).

## References

Bonett, D. G., Wright, T. A. (2000). Sample size requirements
for estimating Pearson, Kendall and Spearman correlations.
*Psychometrika, 65*, 23-28.

Bonett, D. G. (2014). CIcorr.R and sizeCIcorr.R
https://people.ucsc.edu/~dgbonett/psyc181.html

Moinester, M., & Gottfried, R. (2014). Sample size estimation for
correlations with pre-specified confidence interval. *The Quantitative
Methods of Psychology, 10*(2), 124-130.
https://www.tqmp.org/RegularArticles/vol10-2/p124/p124.pdf

Peters, G. J. Y. & Crutzen, R. (forthcoming) An easy and foolproof method
for establishing how effective an intervention or behavior change method is:
required sample size for accurate parameter estimation in health psychology.

## Author

Douglas Bonett (UC Santa Cruz, United States), with minor edits by
Murray Moinester (Tel Aviv University, Israel) and Gjalt-Jorn Peters (Open
University of the Netherlands, the Netherlands).

Maintainer: Gjalt-Jorn Peters gjalt-jorn@userfriendlyscience.com

## Examples

```
### To request confidence intervals for one correlation
confIntR(.3, 100);
#> lo hi
#> 0.3 0.1100677 0.4687942
#> attr(,"r")
#> [1] 0.3
#> attr(,"N")
#> [1] 100
#> attr(,"conf.level")
#> [1] 0.95
### The lower bound of a single correlation
confIntR(.3, 100)[1];
#> [1] 0.1100677
### To request confidence intervals for multiple correlations:
confIntR(c(.1, .3, .5), 250);
#> lo hi
#> 0.1 -0.02436935 0.2213211
#> 0.3 0.18273439 0.4088496
#> 0.5 0.40079576 0.5876152
#> attr(,"r")
#> [1] 0.1 0.3 0.5
#> attr(,"N")
#> [1] 250
#> attr(,"conf.level")
#> [1] 0.95
### The upper bound of the correlation of .5:
confIntR(c(.1, .3, .5), 250)['0.5', 'hi'];
#> [1] 0.5876152
```