print.mitml <- function(x, ...){
# print method for objects of class "mitml"
cl <- x$call
vrs <-x$model
itr <- x$iter
ngr <- length(unique(attr(x$data, "group")))
isML <- attr(x$model, "is.ML")
isL2 <- attr(x$model, "is.L2")
cat("\nCall:\n", paste(deparse(cl)), sep = "\n")
cat("\n")
if(isL2) cat("Level 1:\n", collapse = "\n")
if(isML) cat(formatC("Cluster variable:", width=-25), vrs$clus, sep = " ", collapse = "\n")
cat(formatC("Target variables:", width=-25), vrs$yvrs, collapse = "\n")
cat(formatC("Fixed effect predictors:", width=-25), vrs$pvrs, collapse = "\n")
if(isML) cat(formatC("Random effect predictors:", width=-25), vrs$qvrs, collapse = "\n")
if(isL2){
cat("\n")
cat(formatC("Level 2:\n", width=-25), collapse = "\n")
cat(formatC("Target variables:", width=-25), vrs$yvrs.L2, collapse = "\n")
cat(formatC("Fixed effect predictors:", width=-25), vrs$pvrs.L2, collapse = "\n")
}
cat("\nPerformed", sprintf("%.0f", itr$burn), "burn-in iterations, and generated", sprintf("%.0f", itr$m),
"imputed data sets,\neach", sprintf("%.0f", itr$iter), "iterations apart.",
if(ngr>1){c("\nImputations were carried out seperately within", sprintf("%.0f", ngr), "groups.\n")}, "\n")
invisible(NULL)
}
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