R_tasks/prepare_PWb.R

In gorkang/jsPsychHelpeR: Standardize and automatize data preparation and analysis of jsPsych experiments created with jsPsychMaker

##' Prepare PWb
##'
##' Template for the functions to prepare specific tasks. Most of this file should not be changed
##' Things to change: 
##'   - Name of function: prepare_PWb -> prepare_[value of short_name_scale_str] 
##'   - dimensions parameter in standardized_names()
##'   - 2 [ADAPT] chunks
##'
##' @title prepare_PWb
##'
##' @param short_name_scale_str 
##' @param DF_clean
##'
##' @return
##' @author gorkang
##' @export
prepare_PWb <- function(DF_clean, short_name_scale_str, output_formats) {

  # DEBUG
  # targets::tar_load_globals()
  # jsPsychHelpeR::debug_function(prepare_PWb)

  
  # [ADAPT]: Items to ignore, reverse and dimensions ---------------------------------------
  # ****************************************************************************
  
  items_to_ignore = c("00") # Ignore these items: If nothing to ignore, keep items_to_ignore = c("00")
  items_to_reverse = c("02", "04", "05", "08", "09", "13", "15", "20", "22", "25", "26", "27", "29", "30", "33", "34", "36") # Reverse these items: If nothing to reverse, keep  items_to_reverse = c("00")
  
  items_dimensions = list(
    Autoaceptacion = c("01", "07", "13", "19", "25", "31"), 
    RelacionesPositivas = c("02", "08", "14", "20", "26", "32"), 
    Autonomia = c("03", "04", "09", "10", "15", "21", "27", "33"), 
    DominioEntorno = c("05", "11", "16", "22", "28", "39"), 
    CrecimientoPersonal = c("24", "30", "34", "35", "36", "37", "38"), 
    PropositoVida = c("06", "12", "17", "18", "23", "29")
  )
  
  
  # [END ADAPT]: ***************************************************************
  # ****************************************************************************
  
  
  # Standardized names ------------------------------------------------------
  names_list = standardized_names(short_name_scale = short_name_scale_str, 
                     dimensions = names(items_dimensions),
                     help_names = FALSE) # help_names = FALSE once the script is ready
  
  # Create long -------------------------------------------------------------
  DF_long_RAW = create_raw_long(DF_clean, short_name_scale = short_name_scale_str, numeric_responses = TRUE, help_prepare = FALSE)
  
  
  # Create long DIR ------------------------------------------------------------
  

  
  DF_long_DIR = 
    DF_long_RAW |> 
   dplyr::select(id, trialid, RAW) |>
    
    
  # [ADAPT]: RAW to DIR for individual items -----------------------------------
  # ****************************************************************************
  
    # Transformations
    dplyr::mutate(
      DIR = RAW
      ) |> 
    
    # Invert items
    dplyr::mutate(
      DIR = 
       dplyr::case_when(
          DIR == 9999 ~ DIR, # To keep the missing values unchanged
          trialid %in% paste0(short_name_scale_str, "_", items_to_reverse) ~ (7 - DIR),
          TRUE ~ DIR
        )
    )
    
  # [END ADAPT]: ***************************************************************
  # ****************************************************************************
    

  # Create DF_wide_RAW_DIR -----------------------------------------------------
  DF_wide_RAW =
    DF_long_DIR |> 
    tidyr::pivot_wider(
      names_from = trialid, 
      values_from = c(RAW, DIR),
      names_glue = "{trialid}_{.value}") |> 
    
    # NAs for RAW and DIR items
    dplyr::mutate(!!names_list$name_RAW_NA := rowSums(is.na(across((-matches(paste0(short_name_scale_str, "_", items_to_ignore, "_RAW")) & matches("_RAW$"))))),
                  !!names_list$name_DIR_NA := rowSums(is.na(across((-matches(paste0(short_name_scale_str, "_", items_to_ignore, "_DIR")) & matches("_DIR$"))))))
        
    
  # [ADAPT]: Scales and dimensions calculations --------------------------------
  # ****************************************************************************
    # [USE STANDARD NAMES FOR Scales and dimensions: name_DIRt, name_DIRd1, etc.] Check with: standardized_names(help_names = TRUE)

  DF_wide_RAW_DIR = 
    DF_wide_RAW |> 
    dplyr::mutate(

      # Score Dimensions (see standardized_names(help_names = TRUE) for instructions)
      !!names_list$name_DIRd[1] := rowSums(across(all_of(paste0(short_name_scale_str, "_", items_dimensions[[1]], "_DIR"))), na.rm = TRUE), 
      !!names_list$name_DIRd[2] := rowSums(across(all_of(paste0(short_name_scale_str, "_", items_dimensions[[2]], "_DIR"))), na.rm = TRUE),
      !!names_list$name_DIRd[3] := rowSums(across(all_of(paste0(short_name_scale_str, "_", items_dimensions[[3]], "_DIR"))), na.rm = TRUE), 
      !!names_list$name_DIRd[4] := rowSums(across(all_of(paste0(short_name_scale_str, "_", items_dimensions[[4]], "_DIR"))), na.rm = TRUE),
      !!names_list$name_DIRd[5] := rowSums(across(all_of(paste0(short_name_scale_str, "_", items_dimensions[[5]], "_DIR"))), na.rm = TRUE),
      !!names_list$name_DIRd[6] := rowSums(across(all_of(paste0(short_name_scale_str, "_", items_dimensions[[6]], "_DIR"))), na.rm = TRUE),
      
      # Score Scale
      !!names_list$name_DIRt := rowSums(across(all_of(matches("_DIR$"))), na.rm = TRUE)
      
    )
    
  # [END ADAPT]: ***************************************************************
  # ****************************************************************************


  # CHECK NAs -------------------------------------------------------------------
  check_NAs(DF_wide_RAW_DIR)
  
  # Save files --------------------------------------------------------------
  save_files(DF_wide_RAW_DIR, short_name_scale = short_name_scale_str, is_scale = TRUE, output_formats = output_formats)
  
  # Output of function ---------------------------------------------------------
  return(DF_wide_RAW_DIR) 
 
}