Nothing
statsBy.boot <- function (data,group,ntrials=10,cors=FALSE,replace=TRUE,method="pearson") { #
cl <- match.call()
result <- vector("list",ntrials) #supposedly allocates more memory
for (i in 1:ntrials) {
progressBar(i,ntrials,"statsBy")
data[,group] <- sample(data[,group],size=nrow(data),replace=replace)
result[[i]] <- statsBy(data,group,cors=cors,method=method)
}
return(result)
}
statsBy.boot.summary <- function(res.list,var="ICC2") {
nreps <- length(res.list)
nvar <- length(res.list[[1]][[var]])
cnames <- names(res.list[[1]][[var]])
temp <- matrix(NaN,ncol=nvar,nrow=nreps)
colnames(temp) <- cnames
for(i in 1:nreps){
temp[i,] <- res.list[[i]][[var]]
}
return(temp)
}
# crossValidate <- function(data,group,ntrials=10,cors=FALSE,replace=FALSE,method="pearson",x,y) {
# cl <- match.call()
# subjects <- 1:nrow(data)
# sub2 <- nrow(data)/2
# result <- vector("list",ntrials) #supposedly allocates more memory
#
# for (i in 1:ntrials) {
# progressBar(i,ntrials,"crossValidate")
# samp <- sample(subjects,size =sub2,replace=replace)
# resultA <- statsBy(data[samp,],group,cors=cors,method=method)
# resultB <- statsBy(data[-samp,],group,cors=cors,method=method)
# result[[i]] <- cor(resultA$mean,resultB,
#
# }
#
#
# }
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