Nothing
# plotCutoffNested: plot the cutoff from the difference in fit indices from two
# models
plotCutoffNested <- function(nested, parent, alpha = 0.05, cutoff = NULL, usedFit = NULL,
useContour = T) {
mod <- clean(nested, parent)
nested <- mod[[1]]
parent <- mod[[2]]
if (!all.equal(unique(nested@paramValue), unique(parent@paramValue)))
stop("Models are based on different data and cannot be compared, check your random seed")
if (!all.equal(unique(nested@n), unique(parent@n)))
stop("Models are based on different values of sample sizes")
if (!all.equal(unique(nested@pmMCAR), unique(parent@pmMCAR)))
stop("Models are based on different values of the percent completely missing at random")
if (!all.equal(unique(nested@pmMAR), unique(parent@pmMAR)))
stop("Models are based on different values of the percent missing at random")
Data <- as.data.frame(nested@fit - parent@fit)
condition <- c(length(unique(nested@pmMCAR)) > 1, length(unique(nested@pmMAR)) >
1, length(unique(nested@n)) > 1)
condValue <- cbind(nested@pmMCAR, nested@pmMAR, nested@n)
colnames(condValue) <- c("Percent MCAR", "Percent MAR", "N")
if (!is.null(alpha)) {
if (all(!condition))
if (is.null(cutoff))
cutoff <- getCutoffDataFrame(Data, alpha)
}
if (sum(condition) == 0) {
plotCutoffDataFrame(Data, cutoff, FALSE, usedFit)
} else if (sum(condition) == 1) {
plotCutoffDataFrame(Data, cutoff, FALSE, usedFit, vector1 = condValue[, condition],
nameVector1 = colnames(condValue)[condition], alpha = alpha)
} else if (sum(condition) == 2) {
condValue <- condValue[, condition]
plotCutoffDataFrame(Data, cutoff, FALSE, usedFit, vector1 = condValue[, 1], vector2 = condValue[,
2], nameVector1 = colnames(condValue)[1], nameVector2 = colnames(condValue)[2],
alpha = alpha, useContour = useContour)
} else {
stop("This function cannot plot when there more than two dimensions of varying parameters")
}
}
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