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# Calculate Effects for term(s) in a Multivariate Linear Model
# 2014-03-12: Introduced allEffects.mlm(). J. Fox
Effect.mlm <- function(focal.predictors, mod, response, ...) {
if (missing(response)) {
mod.frame <- model.frame(mod)
response <- colnames(model.response(mod.frame))
}
else if (is.numeric(response)) {
mod.frame <- model.frame(mod)
response.names <- colnames(model.response(mod.frame))
response <- response.names[response]
}
if (length(response)==1) {
mod.1 <- update(mod, as.formula(paste(response, " ~ .")))
result <- Effect(focal.predictors, mod.1, ...)
}
else {
result <- as.list(NULL)
for (resp in response) {
mod.1 <- update(mod, as.formula(paste(resp, " ~ .")))
lab <- resp
result[[lab]] <- Effect(focal.predictors, mod.1, ...)
}
class(result) <- "efflist"
}
result
}
allEffects.mlm <- function(mod, ...){
result <- NextMethod()
class(result) <- "mlm.efflist"
result
}
plot.mlm.efflist <- function(x, ...){
x <- do.call(c, x)
class(x) <- "efflist"
plot(x, ...)
}
summary.mlm.efflist <- function(object, ...){
object <- do.call(c, object)
for (effect in names(object)){
cat("\n\nResponse:", object[[effect]]$response, "\n")
print(summary(object[[effect]], ...))
}
}
print.mlm.efflist <- function(x, ...){
x <- do.call(c, x)
for (effect in names(x)){
cat("\n\nResponse:", x[[effect]]$response, "\n")
print(x[[effect]], ...)
}
invisible(x)
}
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