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#' Extract the information from the simulation data frame to analyse the individual conditional expectation
#'
#' @param allsim dataset with all simulations values
#' @param dataset dataset with all variables
#' @param dr a vector with dose response values
#' @param squem squeme of the values of the prediction values
#' @param remove_extrem boolean parameter to remove the extrem values
#' @return a data frame with interactions
#' @examples
#' data(expose_data)
#' data(simu)
#' data(gen)
#' delta=c(1,0)
#' seku <- seq(0,1,0.05)
#' Exposures<- c('Var1','Var2','Var3','Var4','Var5')
#' summary_table_lines <- gen[[2]]
#' ice_res <- ice(allsim = simu[[1]], dataset = expose_data, dr = seku,
#' squem = summary_table_lines, remove_extrem = FALSE)
#' @export
ice <- function(allsim, dataset, dr = seq(0, 1, 0.1), squem, remove_extrem = FALSE) {
ext <- squem[grep("DR_", squem$Group), ]
hm_pol <- unique(ext$Case)
n <- nrow(dataset)
ext2 <- ext[ext$Case == hm_pol[1], ]
df <- data.frame(allsim)
ini <- ext2$From[1]
fin <- ext2$To[nrow(ext2)]
allpcb <- data.frame(df[ini:fin, 1])
allpcb$id <- rep(1:nrow(dataset), length(dr))
mm <- NULL
len2 <- length(dr) - 1
for (g in 0:len2) {
mm <- c(mm, rep(g, n))
}
allpcb$X <- mm
names(allpcb)[1] <- paste0(hm_pol[1], "_pred")
if (length(hm_pol) > 1) {
hm_pol2 <- hm_pol[-1]
for (h in hm_pol2) {
# extracting again for each pollutant
ext2 <- ext[ext$Case == h, ]
df <- data.frame(allsim)
ini <- ext2$From[1]
fin <- ext2$To[nrow(ext2)]
allpcb2 <- data.frame(df[ini:fin, 1])
allpcb2$id <- rep(1:nrow(dataset), length(dr))
allpcb2$X <- mm
names(allpcb2)[1] <- paste0(h, "_pred")
allpcb <- merge(allpcb, allpcb2, by = c("id", "X"))
}
}
ice <- merge(dataset, allpcb, by = "id")
seku_breaks <- as.character(sort(as.numeric(as.character(unique(ice$X)))))
ice$X <- factor(ice$X, levels = seku_breaks)
if (remove_extrem) {
sekut <- dr[c(1, length(dr))]
ice <- ice[!ice$X %in% sekut, ]
}
return(ice)
}
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