corrZ2ophi {CorrToolBox} | R Documentation |
Computation of the Ordinal Phi Coefficient from the Correlation of Bivariate Standard Normal Variables
Description
This is an intermediate function that utilizes mps2cps
to transform the specified marginal probabilities into cumulative probabilities and uses the contord
function in the GenOrd
package to compute the ordinal phi coefficient derived from discretizing bivariate standard normal variables.
Usage
corrZ2ophi(corrZ, p1, p2)
Arguments
corrZ |
The correlation of two standard normal variables. |
p1 |
A numeric vector containing marginal probabilities defining categories for the first ordinal variable. |
p2 |
A numeric vector containing marginal probabilities defining categories for the second ordinal variable. |
Value
The ordinal phi coefficient.
References
Demirtas, H., Ahmadian, R., Atis, S., Can, F.E., and Ercan, I. (2016). A nonnormal look at polychoric correlations: modeling the change in correlations before and after discretization. Computational Statistics, 31(4), 1385-1401.
Ferrari, P.A. and Barbiero, A. (2012). Simulating ordinal data. Multivariate Behavioral Research, 47(4), 566-589.
See Also
Examples
set.seed(567)
library(moments)
y1<-rweibull(n=100000, scale=1, shape=3.6)
y1.skew<-round(skewness(y1), 5)
y1.exkurt<-round(kurtosis(y1)-3, 5)
gaussmix <- function(n,m1,m2,s1,s2,pi) {
I <- runif(n)<pi
rnorm(n,mean=ifelse(I,m1,m2),sd=ifelse(I,s1,s2))
}
y2<-gaussmix(n=100000, m1=0, s1=1, m2=2, s2=1, pi=0.3)
y2.skew<-round(skewness(y2), 5)
y2.exkurt<-round(kurtosis(y2)-3, 5)
corrZ2ophi(corrZ=0.502, p1=c(0.4, 0.3, 0.2, 0.1), p2=c(0.2, 0.2, 0.6))