R/mvn_mar_30_dat.R

Defines functions mvn_mar_30_dat_simulation mvn_mar_30_dat_task mvn_mar_30_dat

Documented in mvn_mar_30_dat mvn_mar_30_dat_simulation mvn_mar_30_dat_task

#' @author Ivan Jacob Agaloos Pesigan
#'
#' @title Generate Data from a Multivariate Normal Distribution
#'   following a Simple Mediation Model
#'   with Data Missing at Random - 30%
#'
#' @family missing at random
#' @keywords mvn_dat
#' @importFrom mice ampute
#' @importFrom stats complete.cases
#' @inheritParams fit.ols
#' @inheritParams useparamsmvn
#' @examples
#' taskid <- 1
#' data <- mvn_dat(taskid = taskid)
#' mvn_mar_30_dat(data = data, taskid = taskid)
#' @export
mvn_mar_30_dat <- function(data,
                           taskid) {
  paramsmvn <- useparamsmvn(taskid = taskid)
  missing <- ampute(
    data,
    prop = 0.30,
    mech = "MAR"
  )
  missing <- as.matrix(
    missing$amp
  )
  colnames(missing) <- c("x", "m", "y")
  attributes(missing)$taskid <- paramsmvn$taskid
  attributes(missing)$n <- paramsmvn$n
  attributes(missing)$n.complete <- nrow(missing[complete.cases(missing), ])
  missing
}

#' @author Ivan Jacob Agaloos Pesigan
#'
#' @title Generate Data from a Multivariate Normal Distribution
#'   following a Simple Mediation Model
#'   with Data Missing at Random - 30%
#'   (Single Task)
#'
#' @family missing at random
#' @keywords mvn_dat
#' @inheritParams mvn_mar_30_dat
#' @inheritParams mvn_dat_task
#' @export
mvn_mar_30_dat_task <- function(taskid,
                                dir = getwd(),
                                overwrite = FALSE) {
  # for socks to load package in the namespace
  requireNamespace(
    "jeksterslabRmedsimple",
    quietly = TRUE
  )
  wd <- getwd()
  setwd(dir)
  fndata <- paste0(
    "medsimple_mvn_dat_",
    sprintf(
      "%05.0f",
      taskid
    ),
    ".Rds"
  )
  fn <- paste0(
    "medsimple_mvn_mar_30_dat_",
    sprintf(
      "%05.0f",
      taskid
    ),
    ".Rds"
  )
  # Check if data exists --------------------------------------------------------
  if (file.exists(fndata)) {
    X <- readRDS(fndata)
  } else {
    stop(
      paste(
        fndata,
        "does not exist in",
        dir
      )
    )
  }
  # Resolve overwrite ---------------------------------------------------------------------------
  if (overwrite) {
    run <- TRUE
  } else {
    # Check if result exists -------------------------------------------------------------
    if (file.exists(fn)) {
      run <- FALSE
      tryCatch(
        {
          existing_results <- readRDS(fn)
        },
        error = function(e) {
          run <- TRUE
        }
      )
    } else {
      run <- TRUE
    }
  }
  if (run) {
    out <- invisible(
      par_lapply(
        X = X,
        FUN = mvn_mar_30_dat,
        taskid = taskid,
        par = FALSE, # should always be FALSE since this is wrapped around a parallel par_lapply
        blas_threads = FALSE # should always be FALSE since this is wrapped around a parallel par_lapply
      )
    )
    saveRDS(
      object = out,
      file = fn
    )
  }
  invisible(
    setwd(wd)
  )
}

#' @author Ivan Jacob Agaloos Pesigan
#'
#' @title Generate Data from a Multivariate Normal Distribution
#'   following a Simple Mediation Model
#'   with Data Missing at Random - 30%
#'   (Simulation)
#'
#' @family missing at random
#' @keywords mvn_dat
#' @importFrom jeksterslabRpar par_lapply
#' @inheritParams mvn_mar_30_dat_task
#' @inheritParams jeksterslabRpar::par_lapply
#' @inheritParams mvn_dat_simulation
#' @export
mvn_mar_30_dat_simulation <- function(dir = getwd(),
                                      all = TRUE,
                                      taskid = NULL,
                                      overwrite = FALSE,
                                      par = TRUE,
                                      ncores = NULL,
                                      blas_threads = TRUE,
                                      mc = TRUE,
                                      lb = FALSE,
                                      cl_eval = FALSE,
                                      cl_export = FALSE,
                                      cl_expr,
                                      cl_vars) {
  if (all) {
    ncase <- nrow(jeksterslabRmedsimple::paramsmvn)
    taskid <- 1:ncase
  } else {
    if (is.null(taskid)) {
      stop(
        "If \`all = FALSE\` \`taskid\` should be provided."
      )
    }
  }
  out <- invisible(
    par_lapply(
      X = taskid,
      FUN = mvn_mar_30_dat_task,
      dir = dir,
      overwrite = overwrite,
      par = par,
      ncores = ncores,
      blas_threads = blas_threads,
      mc = mc,
      lb = lb,
      cl_eval = cl_eval,
      cl_export = cl_eval,
      cl_expr = cl_expr,
      cl_vars = cl_vars,
      rbind = NULL
    )
  )
}
jeksterslabds/jeksterslabRmedsimple documentation built on Oct. 16, 2020, 11:30 a.m.