Visualize Frank Tablet Data

---

TIMEPOINTS_PATH <- here("data/frank_tablet_2016/processed_data/aoi_timepoints.csv")
aoi_timepoints <- read_csv(TIMEPOINTS_PATH)

TRIALS_PATH <- here("data/frank_tablet_2016/processed_data/trials.csv")
trials <- read_csv(TRIALS_PATH)

ADMINS_PATH <-here("data/frank_tablet_2016/processed_data/administrations.csv")
admins <- read_csv(ADMINS_PATH) %>%
  select(administration_id, age)

STIMULI_PATH <-here("data/frank_tablet_2016/processed_data/stimuli.csv")
stimuli <- read_csv(STIMULI_PATH) %>%
  select(stimulus_id, stimulus_novelty)
  
df <- aoi_timepoints %>%
  left_join(trials) %>%
  left_join(admins) %>%
  left_join(stimuli, by = c("target_id" = "stimulus_id"))

prop_correct_by_trial <- df %>%
  filter(age > 12, age <= 60) %>%
  mutate(age_binned = cut(age, seq(0,60,12))) %>%
  filter(aoi %in% c("distractor", "target")) %>%
  group_by(t_norm, age_binned, stimulus_novelty) %>%
  summarize(p = sum(aoi == "target", na.rm = TRUE),
            prop_correct = p/n()) 

ggplot(prop_correct_by_trial, aes(x = t_norm, y = prop_correct, color = age_binned)) +
    geom_line() +
    facet_wrap(stimulus_novelty ~ .) +
    geom_hline(yintercept = .5, lty = 2) +
    geom_vline(xintercept = 0, lty = 2) +
    ylab("Proportion Target Looking") +
    xlab("Time (msec)") +
    theme_classic()