Nothing
mzv.test <- function (formula, data, 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 <- "Modified Z Variance 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)
y.variance <- tapply(y, group, var)
y.means <- tapply(y, group, mean)
ni<- tapply(y, group, length)
g<- list()
for (i in x.levels) {
g[[i]] <- (y[group==i]-y.means[i])/sqrt(((ni[i]-1)/ni[i])*y.variance[i])
}
g_total<- unlist(lapply(1:k, function(i) sum(g[[i]]^4)))
K<- g_total/(ni-2)
ci <- 2*(((2.9+0.2/ni)/mean(K))^((1.6*(ni-1.8*K+14.7))/ni))
z<- list()
for (i in x.levels) {
z[[i]]<- sum((y[group==i]-y.means[i])^2)
}
mse_nom <- sum(unlist(z))
MSE<- mse_nom/(n-k)
zi_left<- sqrt((ci*(ni-1)*y.variance)/MSE)
zi_right<- sqrt(ci*(ni-1)-(ci/2))
zi<- as.numeric(zi_left - zi_right)
vtest<- sum(zi^2)/(k-1)
df1 = k-1
df2 = Inf
p.value = pf(vtest, 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 :", vtest, "\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$statistic <- vtest
result$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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