R/prepare.R

In netmeta: Network Meta-Analysis using Frequentist Methods

prepare <- function(TE, seTE, treat1, treat2, studlab, tau = 0,
                    func.inverse) {
  
  if (is.na(tau))
    tau <- 0
  
  weights <- 1 / (seTE^2 + tau^2)
  
  data <- data.frame(studlab,
                     treat1, treat2,
                     treat1.pos = NA, treat2.pos = NA,
                     TE, seTE, weights,
                     narms = NA, stringsAsFactors = FALSE)
  ##
  ## Ordering data set
  ##
  o <- order(data$studlab, data$treat1, data$treat2)
  data <- data[o, ]
  ##
  ## Adapt numbers to treatment IDs
  ##
  names.treat <- sort(unique(c(data$treat1, data$treat2)))
  data$treat1.pos <- match(data$treat1, names.treat)
  data$treat2.pos <- match(data$treat2, names.treat)
  
  newdata <- data[1, ][-1, ]
  ##
  sl <- unique(data$studlab)
  ##
  ## Determining number of arms and adjusting weights of
  ## multi-arm studies
  ##
  for (s in sl) {
    subgraph <- data[data$studlab == s, ]
    subgraph$narms <- (1 + sqrt(8 * dim(subgraph)[1] + 1)) / 2
    ## Reciprocal new weights
    if (dim(subgraph)[1] > 1)
      subgraph$weights <-
        1 / multiarm(1 / subgraph$weights, s, func.inverse)$v
    ##
    newdata <- rbind(newdata, subgraph)
  }
  res <- newdata
  ##
  res$order <- o
  ##
  res
}