hist_levels <- function(VAR, LAB, dat1, dat2, grouping, mfrow = c(2, 2), ...) {
cat("Classification by ", grouping, "\n")
n.var <- length(VAR)
av <- as.matrix(cbind(dat1[, VAR]))
UV <- factor(dat1[, grouping])
res1 <- aggregate(av ~ UV, data = dat1, FUN = mean, na.rm = TRUE)
av <- as.matrix(cbind(dat2[, VAR]))
UV <- factor(dat2[, grouping])
res2 <- aggregate(av ~ UV, data = dat2, FUN = mean, na.rm = TRUE)
res <- merge(res1, res2, by = "UV")
res2 <- res[, 1:(n.var + 1)]
for (i in 2:(n.var + 1)) {
res2[i] <- res[i] - res[i + n.var]
}
op <- par(mfrow = mfrow)
for (i in 2:(n.var + 1)) {
hist(res2[, i], main = LAB[i - 1], labels = TRUE, xlab = "d", ylab = "Frequency", col = "grey", ...)
abline(v = c(-0.5, 0, 0.5), lty = c(2, 1, 2))
}
par(op)
}
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