print.mitml.anova <- function(x, digits = 3, sci.limit = 5, ...){
# print method for anova method
cll <- x$call
test <- x$test
fml <- x$formula
method <- x$method
data <- x$data
ariv <- x$ariv
order.method <- x$order.method
use <- x$use
reml <- x$reml
m <- x$test[[1]]$m
n.tests <- length(fml)
# print header
cat("\nCall:\n", paste(deparse(cll)), sep = "\n")
cat("\nModel comparison calculated from", m, "imputed data sets.")
# print method
cat("\nCombination method:", method)
if(method == "D2") cat(" (", use, ")", sep = "")
if(method == "D4" && ariv == "robust") cat(" (robust)", sep = "")
cat("\n")
# print model formulas
cat("\n")
for(mm in seq.int(1, n.tests)) cat("Model ", mm, ": ", fml[mm], "\n", sep = "")
cat("\n")
# combine multiple tests in one table
test.tab <- lapply(test, "[[", "test")
test.tab <- do.call(rbind, test.tab)
rn <- paste0(seq.int(1, n.tests - 1), " vs ", seq.int(2, n.tests), " ")
rownames(test.tab) <- rn
# format table
test.digits <- c(digits, 0, rep(digits, ncol(test.tab)-2))
out <- .formatTable(test.tab, digits = test.digits, sci.limit = sci.limit)
for(i in seq_len(nrow(out))) cat(" ", out[i,], "\n")
cat("\n")
# print footer
if(is.null(order.method)){
cat("Models were ordered as provided by the user (by decreasing complexity).\n")
}else{
cat("Models were automatically ordered via '", order.method, "' (by decreasing complexity).\n", sep = "")
}
if(method == "D4"){
if(data){
cat("Data for stacking were extracted from the `data` argument.\n")
}else{
cat("Data for stacking were automatically extracted from the fitted models.\n")
}
}
if(reml){
cat("Models originally fit with REML were automatically refit using ML.\n")
}
cat("\n")
invisible()
}
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