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# Computes the correlation between observed and imputed observations
# Arguments:
# object is of class yai or yai.impute If the object is yai, impute is called
# with observed=TRUE.
# vars is a list of variables, if NULL, all those with imputed values are processed.
# ... passed to the impute funciton when it is called
cor.yai = function (object,vars=NULL,...)
{
if (missing(object)) stop ("object required.")
if (class(object)[1] == "yai") object = impute.yai(object,vars=vars,observed=TRUE,...)
if (is.null(object)) stop ("no imputations found using this object")
object=na.omit(object)
if (is.null(vars)) vars=names(object)
vi=paste(unique(strsplit(vars,".o",fixed=TRUE)))
vi=intersect(vi,names(object))
notFound=setdiff(vars,names(object))
if (length(notFound)>0) warning ("variables not found: ",paste(notFound,collapse=", "))
if (length(vi) == 0) stop("nothing to compute")
vo=paste(vi,"o",sep=".")
notFound=setdiff(vo,names(object))
if (length(notFound)>0) warning ("variables not found: ",paste(notFound,collapse=", "))
vo=intersect(vo,names(object))
both=intersect(paste(unique(strsplit(vo,".o",fixed=TRUE))),vi)
if (length(both) == 0) stop("nothing to compute")
vo=paste(both,"o",sep=".")
cors=data.frame(rep(NA,length(vo)),row.names=both)
names(cors)="r"
for (i in 1:length(both)) if (!is.factor(object[,both[i]]))
cors[i,1]=cor(object[,both[i]],object[,vo[i]])
cors
}
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