Description Usage Arguments Value References See Also Examples
View source: R/IntermediateONN.R
This function computes the intermediate correlation values of pairwise correlations between binary/ordinal and continuous variables.
1 | IntermediateONN(plist, skew.vec, kurto.vec, ONNCorrMat)
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plist |
A list of probability vectors corresponding to each binary/ordinal variable. The i-th element of |
skew.vec |
The skewness vector for continuous variables. |
kurto.vec |
The kurtosis vector for continuous variables. |
ONNCorrMat |
A matrix of pairwise target (point-biserial/polyserial) correlations between binary/ordinal and continuous variables. This is a submatrix of the overall correlation matrix, and it is pertinent to the binary/ordinal-continuous part. Hence, the matrix may or may not be square. Even when it is square, it may not be symmetric. |
A pairwise correlation matrix of intermediate correlations, where rows and columns represent continuous and binary/ordinal variables, respectively.
Demirtas, H., Hedeker, D., and Mermelstein, R.J. (2012). Simulation of massive public health data by power polynomials. Statistics in Medicine, 31(27), 3337-3346.
Demirtas, H. and Hedeker, D. (2016). Computing the point-biserial correlation under any underlying continuous distribution. Communications in Statistics - Simulation and Computation, 45(8), 2744-2751.
IntermediateNonNor
, cmat.star.BinOrdNN
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | no.bin <- 1
no.ord <- 2
no.NN <- 4
q <- no.bin + no.ord + no.NN
set.seed(54321)
Sigma <- diag(q)
Sigma[lower.tri(Sigma)] <- runif((q*(q-1)/2),-0.4,0.4)
Sigma <- Sigma + t(Sigma)
diag(Sigma) <- 1
marginal <- list(0.3, cumsum( c(0.30, 0.40) ), cumsum(c(0.4, 0.2, 0.3) ) )
ONNCorrMat <- Sigma[4:7, 1:3]
IntermediateONN(marginal, skew.vec=c(1,2,2,3), kurto.vec=c(2,7,25,25), ONNCorrMat)
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