correlation-tools {rapidsplithalf} | R Documentation |
Helper functions to compute important statistics from correlation coefficients.
r2z(r)
z2r(z)
r2t(r, n)
t2r(t, n)
r2p(r, n)
rconfint(r, n, alpha = 0.05)
compcorr(r1, r2, n1, n2)
## S3 method for class 'compcorr'
print(x, ...)
r , r1 , r2 |
Correlation values. |
z |
Z-scores. |
n , n1 , n2 |
Sample sizes. |
t |
t-scores. |
alpha |
The significance level to use. |
x |
A |
... |
Ignored. |
For r2z()
, z2r
, r2t
, t2r
, and r2p
,
a numeric vector with the requested transformation applied.
For rconfint()
, a numeric vector with two values representing
the lower and upper confidence intervals of the correlation coefficient.
For compcorr()
, a compcorr
object containing
a z and p value for the requested comparison,
which can be printed with print.compcorr()
.
r2z()
: Converts correlation coefficients to z-scores.
z2r()
: Converts z-scores to correlation coefficients.
r2t()
: Converts correlation coefficients to t-scores.
t2r()
: Converts t-scores to correlation coefficients.
r2p()
: Computes the two-sided p-value for a given correlation.
rconfint()
: Computes confidence intervals for one or multiple correlation coefficients.
compcorr()
: Computes the significance of the difference between two correlation coefficients.
print(compcorr)
: Computes the significance of the difference between two correlation coefficients.
z <- r2z(.5)
r <- z2r(z)
t<-r2t(r,30)
r<-t2r(t,30)
r2p(r,30)
print(rconfint(r,30))
print(compcorr(.5,.7,20,20))