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summary.fittedlooplist2r <- function(object,N=1000,boot=TRUE,seed=NULL,...) {
g <- object
summarycall <- match.call()
if (!is.null(seed)) set.seed(seed)
if (boot==TRUE) {
res <- mapply(summary.loop2r,g$models,MoreArgs=list(N=N,boot=TRUE,...),SIMPLIFY=FALSE)
values <- do.call("rbind",lapply(res,function (x)
data.frame("Parameter"= rownames(x$values),x$values)))
rownames(values) <- NULL
if (length(dim(g$models))==1) {
thesubjects <- rep(rownames(g$Estimates),each=length(g$models[[1]]$values))
values <- cbind("Subject"=thesubjects,values)
Estimates <- matrix(values[,"Boot.Estimate"],nrow=length(g$Estimates[,1]),byrow=TRUE)
rownames(Estimates) <- rownames(g$Estimates)
colnames(Estimates) <- names(g$models[[1]]$values)
Std.Error <- matrix(values[,"Std.Error"],nrow=length(g$Estimates[,1]),byrow=TRUE)
rownames(Std.Error) <- rownames(g$Estimates)
colnames(Std.Error) <- names(g$models[[1]]$values)}
else {
length.values <- length(g$models[[1]]$values)
subjectlen <- length(colnames(g$Estimates))-length.values
subjectdata <- apply(g$Estimates[,1:subjectlen],2,rep,each=length.values)
colnames(subjectdata) <- colnames(g$Estimates)[1:subjectlen]
values <- cbind(subjectdata,values)
Estimates <- matrix(values[,"Boot.Estimate"],nrow=length(g$Estimates[,1]),byrow=TRUE)
Estimates <- cbind(g$Estimates[,1:subjectlen],Estimates)
colnames(Estimates) <- c(colnames(subjectdata),names(g$models[[1]]$values))
Std.Error <- matrix(values[,"Std.Error"],nrow=length(g$Estimates[,1]),byrow=TRUE)
Std.Error <- cbind(g$Estimates[,1:subjectlen],Std.Error)
colnames(Std.Error) <- c(colnames(subjectdata),names(g$models[[1]]$values))
dim(res) <- dim(g$models)
dimnames(res) <- dimnames(g$models)
}
res <- list("models"=res,"values"=values,"Boot.Estimates"=Estimates,"Boot.Std.Errors"=Std.Error,"Delta.Std.Errors"=g$Std.Errors)
res$summarycall <- summarycall
class(res) <- "loopsummarylist2r"}
else res <- g
res
}
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