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STATSboot <-function(X,z,start,lambda1,lambda2,estimation,out){
items <- colnames(X)
dat <- X[z,]
if (any(is.na(dat))){
mice_dat <- data.frame(sapply(dat, as.factor))
new.pred <- quickpred(mice_dat, method = 'kendall', mincor = out$CALL$mincor)
mice_imp <- mice(mice_dat,1, method = 'myfunc', printFlag = FALSE, predictorMatrix = new.pred, maxit = 20)
mdat <- complete(mice_imp,1)
dat <- data.frame(sapply(mdat,function(y) as.numeric(levels(y))[y]))
}
dat <- apply(dat, 2, function(x){
if (any(is.na(x))){
x[is.na(x)] <- getmode(x)
}
x
})
fit <- mudfold(dat, start.scale = start,lambda1 = lambda1,lambda2 = lambda2, estimation = estimation,nboot = NULL)
stats_list_scale <- lapply(vector("list", 6 ),function(x) x <- NA)
stats_list_Hitems <- lapply(vector("list", length(items)),function(x) x <- NA)
stats_list_ISOitems <- lapply(vector("list", length(items)),function(x) x <- NA)
stats_list_MAXitems <- lapply(vector("list", length(items)),function(x) x <- NA)
stats_list_EOitems <- lapply(vector("list", length(items)),function(x) x <- NA)
stats_list_Oitems <- lapply(vector("list", length(items)),function(x) x <- NA)
if (!is.null(fit$MUDFOLD_INFO$second_step$scale)){
vecH <- rep(NA,length(items))
vecsH <- rep(NA,length(items))
vecISO <- rep(NA,length(items))
vecMAX <- rep(NA,length(items))
vecEO <- rep(NA,length(items))
vecO <- rep(NA,length(items))
stats_list_scale[[1]] <- paste(fit$MUDFOLD_INFO$second_step$scale,collapse = " ")
stats_list_scale[[2]] <- fit$MUDFOLD_INFO$second_step$Hscale
stats_list_scale[[3]] <- fit$MUDFOLD_INFO$second_step$ISOscale
stats_list_scale[[4]] <- fit$MUDFOLD_INFO$second_step$MAXscale
stats_list_scale[[5]] <- fit$MUDFOLD_INFO$second_step$EXPscale
stats_list_scale[[6]] <- fit$MUDFOLD_INFO$second_step$OBSscale
mdf_items <- fit$MUDFOLD_INFO$second_step$scale
ids <- match(mdf_items,items)
vecH[ids] <- fit$MUDFOLD_INFO$second_step$Hitem
vecISO[ids] <- fit$MUDFOLD_INFO$second_step$ISOitem
vecMAX[ids] <- fit$MUDFOLD_INFO$second_step$MAXitem
vecEO[ids] <- fit$MUDFOLD_INFO$second_step$EXPitem
vecO[ids] <- fit$MUDFOLD_INFO$second_step$OBSitem
for (i in ids){
stats_list_Hitems[[i]] <- vecH[i]
stats_list_ISOitems[[i]] <- vecISO[i]
stats_list_MAXitems[[i]] <- vecMAX[i]
stats_list_EOitems[[i]] <- vecEO[i]
stats_list_Oitems[[i]] <- vecO[i]
}
}
stats <- do.call(cbind,
c(stats_list_scale,
stats_list_Hitems,
stats_list_ISOitems,
stats_list_MAXitems,
stats_list_EOitems,
stats_list_Oitems))
return(stats)
}
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