R/summary_quick_tapping.R

In nelsonroque/surveydolphinr: Scoring and Summarizing of Cognitive task data from an early variant of the Mobile Monitoring of Cognitive Change Project (M2C2) platform.

#' RM2C2: Scoring, Summarizing

#' @name summary_quick_tapping
#' @export
summary_quick_tapping <- function(df, group_var) {
  PACKAGE.VERSION <- packageVersion("RM2C2")
  TASK_NAME <- "QUICK_TAPPING"
  
  summary.df <- df %>%
    group_by_(.dots = group_var) %>%
    summarise(median.acceleration = median(acceleration, na.rm = T),
              mean.acceleration = mean(acceleration, na.rm = T),
              sd.acceleration = sd(acceleration, na.rm = T),
              sd.abs.acceleration = sd(abs(acceleration), na.rm = T),
              max.acceleration = max(acceleration, na.rm = T),
              q90.acceleration = quantile(acceleration, .90, na.rm=T)[[1]][1],
              q95.acceleration = quantile(acceleration, .95, na.rm=T)[[1]][1],
              median.velocity = median(velocity, na.rm = T),
              mean.velocity = mean(velocity, na.rm = T),
              sd.velocity = sd(velocity, na.rm = T),
              max.velocity = max(velocity, na.rm = T),
              q90.velocity = quantile(velocity, .90, na.rm=T)[[1]][1],
              q95.velocity = quantile(velocity, .95, na.rm=T)[[1]][1],
              n.correct.taps = sum(correct_circle_tap == 1),
              n.correct.left_taps = sum(correct_circle_tap == 1 & target_circle == "LEFT"),
              n.correct.right_taps = sum(correct_circle_tap == 1 & target_circle == "RIGHT"),
              n.target.left_taps = sum(target_circle == "LEFT"),
              n.target.right_taps = sum(target_circle == "RIGHT"),
              n.total.taps = n()) %>%
    mutate(prop.correct.left_taps = n.correct.left_taps/n.target.left_taps,
           prop.correct.right_taps = n.correct.right_taps/n.target.right_taps,
           prop.correct.taps = n.correct.taps/n.total.taps)

  summary2.df <- df %>%
    group_by_(.dots = group_var) %>%
    select(c(1:19)) %>%
    summarise(median.first_tap_time = median(first_tap_time, na.rm=T),
              mean.first_tap_time = median(first_tap_time, na.rm=T),
              sd.first_tap_time = sd(first_tap_time, na.rm=T),
              min.first_tap_time = min(first_tap_time, na.rm=T),
              max.first_tap_time = max(first_tap_time, na.rm=T),
              
              median.total_taps = median(total_taps, na.rm=T),
              mean.total_taps = mean(total_taps, na.rm=T),
              sum.total_taps = sum(total_taps, na.rm=T),
              sd.total_taps = sd(total_taps, na.rm=T),
              min.total_taps = min(total_taps, na.rm=T),
              max.total_taps = max(total_taps, na.rm=T),
              
              median.outbounds_taps = median(out_bounds_taps, na.rm=T),
              mean.outbounds_taps = mean(out_bounds_taps, na.rm=T),
              sum.outbounds_taps = sum(out_bounds_taps, na.rm=T),
              sd.outbounds_taps = sd(out_bounds_taps, na.rm=T),
              min.outbounds_taps = min(out_bounds_taps, na.rm=T),
              max.outbounds_taps = max(out_bounds_taps, na.rm=T),
              
              median.repeat_taps = median(repeat_taps, na.rm=T),
              mean.repeat_taps = mean(repeat_taps, na.rm=T),
              sum.repeat_taps = sum(repeat_taps, na.rm=T),
              sd.repeat_taps = sd(repeat_taps, na.rm=T),
              min.repeat_taps = min(repeat_taps, na.rm=T),
              max.repeat_taps = max(repeat_taps, na.rm=T),
              
              n.trials = n())
  
  # add task name to column names
  len_group_var = length(group_var)
  names(summary.df)[(len_group_var+1):ncol(summary.df)] <- paste0(TASK_NAME,".",names(summary.df)[(len_group_var+1):ncol(summary.df)])
  names(summary2.df)[(len_group_var+1):ncol(summary2.df)] <- paste0(TASK_NAME,".",names(summary2.df)[(len_group_var+1):ncol(summary2.df)])
  
  final.df <- merge(summary.df,summary2.df)  %>%
    mutate(PACKAGE.VERSION = PACKAGE.VERSION)
  
  return(final.df)
}