Nothing
levene.test<-function (formula, data, center = "mean", deviation = "absolute", trim.rate = 0.25, alpha = 0.05, na.rm = TRUE, verbose = TRUE)
{
data <- model.frame(formula, data)
dp <- as.character(formula)
DNAME <- paste(dp[[2L]], "and", dp[[3L]])
METHOD <- "Levene's Test"
if (na.rm) {
completeObs <- complete.cases(data)
data <- data[completeObs, ]
}
if (any(colnames(data) == dp[[3L]]) == FALSE)
stop("The name of group variable does not match the variable names in the data. The group variable must be one factor.")
if (any(colnames(data) == dp[[2L]]) == FALSE)
stop("The name of response variable does not match the variable names in the data.")
y = data[[dp[[2L]]]]
group = data[[dp[[3L]]]]
if (!(is.factor(group) | is.character(group)))
stop("The group variable must be a factor or a character.")
if (is.character(group))
group <- as.factor(group)
if (!is.numeric(y))
stop("The response must be a numeric variable.")
n <- length(y)
x.levels <- levels(factor(group))
k <- length(x.levels)
if(center=="mean"){y.means <- tapply(y, group, mean)
}else if(center=="median"){y.means <- tapply(y, group, median)
}else if(center=="trim.mean"){y.means <- tapply(y, group, mean, trim = trim.rate)
}else {stop("Please correct center option.")
}
y.mean <- mean(y)
z <- list()
for(i in x.levels) {
if(deviation=="absolute"){ z[[i]] <- abs(y[group==i]-y.means[i])
}else if(deviation=="squared"){ z[[i]] <- (y[group==i]-y.means[i])^2
}else stop("Please correct deviation type.")
}
z.means <- unlist(lapply(1:k, function(i) mean(z[[i]])))
z.mean <- mean(unlist(lapply(1:k, function(i) z[[i]])))
z.n <- unlist(lapply(1:k, function(i) length(z[[i]])))
nom <- (n-k)*sum(z.n*((z.means-z.mean)^2))
z_gstotal <- unlist(lapply(1:k, function(i) sum((z[[i]]-mean(z[[i]]))^2)))
denom <- (k-1)*sum((z_gstotal))
Ltest= nom/denom
df1 = k-1
df2 = n-k
p.value = pf(Ltest, df1, df2, lower.tail = F)
if (verbose) {
cat("\n", "", METHOD, paste("(alpha = ", alpha, ")",
sep = ""), "\n", sep = " ")
cat("-------------------------------------------------------------",
"\n", sep = " ")
cat(" data :", DNAME, "\n\n", sep = " ")
cat(" statistic :", Ltest, "\n", sep = " ")
cat(" num df :", df1, "\n", sep = " ")
cat(" denom df :", df2, "\n", sep = " ")
cat(" p.value :", p.value, "\n\n", sep = " ")
cat(if (p.value > alpha) {
" Result : Variances are homogeneous."
}
else {
" Result : Variances are not homogeneous."
}, "\n")
cat("-------------------------------------------------------------",
"\n\n", sep = " ")
}
result <- list()
result$statistic <- Ltest
result$parameter <- c(df1, df2)
result$p.value <- p.value
result$alpha <- alpha
result$method <- METHOD
result$data <- data
result$formula <- formula
invisible(result)
}
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