# Computation of Normal Scores for Multivariate Data This function assigns a normal score to binary and ordinal variables using normal quantiles in this appropriate range dictated by marginal proportions; a normal score to count variables based on the equivalence of CDFs of Poisson and normal distribution in the appropriate range dictated by the rate parameters; and a normal score for each continuous measurement by finding the normal root in the Fleishman equation. ```r MVN.dat(ord.info=NULL, nct.info=NULL, count.info=NULL) ``` ## Arguments - `ord.info`: A list containing binary and ordinal data and corresponding marginal probabilities as packaged in `ordmps`. Default is NULL. - `nct.info`: A list containing standardized continuous data and corresponding summary statistics for continuous variables as packaged in `nctsum`. Default is NULL. - `count.info`: A list containing count data and corresponding rates as packaged in `countrate`. Default is NULL. ## Returns A matrix containing normal scores for each variable input. ## References Fleishman A.I. (1978). A method for simulating non-normal distributions. **Psychometrika**, 43(4) , 521-532. ## See Also `MI`, `ordmps`, `nctsum`, `countrate` ## Examples ```r library(PoisBinOrdNonNor) n<-1e4 lambdas<-list(1) mps<-list(c(.2, .8)) moms<-list(c(-1, 1, 0, 1)) #generate Poisson, ordinal, and continuous data cmat.star <- find.cor.mat.star(cor.mat = .8 * diag(3) + .2, no.pois = length(lambdas), no.ord = length(mps), no.nonn = length(moms), pois.list = lambdas, ord.list = mps, nonn.list = moms) mydata <- genPBONN(n, no.pois = length(lambdas), no.ord = length(mps), no.nonn = length(moms), cmat.star = cmat.star, pois.list = lambdas, ord.list = mps, nonn.list = moms) #set a sample of each variable to missing mydata<-apply(mydata, 2, function(x) { x[sample(1:n, size=n/10)]<-NA return(x) }) mydata<-data.frame(mydata) #get information for use in function count.info<-countrate(count.dat=data.frame(mydata[,c('X1')])) ord.info<-ordmps(ord.dat=data.frame(mydata[,c('X2')])) nct.info<-nctsum(nct.dat=data.frame(mydata[,c('X3')])) mvn.dat<-MVN.dat(ord.info=ord.info, nct.info=nct.info, count.info=count.info) #outputs in order of continuous, ordinal, count ```

MVN.dat function