R/prep_data.r

In lebebr01/metaRmat: Synthesis of Correlation Matrices

#' Prep Data for Metafor
#'
#' @param data Raw data input
#' @param n Sample size
#' @param type type of adjustment (olkin siotani)
#' @param missing What to do with missing data
#' @param variable_names An optional character vector specifying variable names
#'   of original data. This is mostly used to pass to \code{\link{df_to_corr}}.
#'   A character vector of variable names representing the columns
#'  to convert to a pairwise correlation matrix. Variable names take the following format:
#'  "columnname_rowname" where the name prior to the underscore is the column name and the
#'  name after the underscore is the row name.
#' @param ID A variable name, as a character string, to use as names for the list elements.
#'
#' @importFrom Matrix bdiag
#' @importFrom corpcor sm2vec
#' @importFrom utils combn
#'
#' @export
prep_data <- function(data, n, type = c('average','weighted', 'simple'),
                      missing = 'remove', variable_names = NULL, ID = NULL) {

  if(is.data.frame(data)) {
    data <- df_to_corr(data, variables = variable_names, ID = ID)
  }

  olkin <- olkin_siotani(data, n, type)

  variance_covariance <- var_cov(olkin)

  data_vector_list <- lapply(data,  corpcor::sm2vec)
  data_vector <-   matrix(unlist(data_vector_list))

  # if(is.null(variable_names)) {
    outcome <- rep(1:length(data_vector_list[[1]]), length(data))
  # } else {
    # outcome <- rep(variable_names, length(data))
  # }
  outcome <- as.factor(outcome)

  study <- sort(rep(1:length(data), length(data_vector_list[[1]])))

  if(!is.null(variable_names)) {
    var_names <- data.frame(t(combn(colnames(becker09_list[[1]]), 2)))
    names(var_names) <- c('Variable1', 'Variable2')
    } else {
    var_names <- NULL
    }


  if(missing == 'remove') {
    miss_loc <- missing_data(data_vector)

    data_vector <- data_vector[miss_loc]
    variance_covariance <- variance_covariance[c(miss_loc), c(miss_loc)]
    outcome <- outcome[miss_loc]
    study <- study[miss_loc]

    if(!is.null(var_names)) {
      var_names <- var_names[miss_loc]
      }

  }

  list(data = cbind(var_names,
                    data.frame(yi = data_vector,
                         outcome = outcome,
                         study = study
  )),
  V = variance_covariance
  )
}