#Read in data
d = read.csv("cat_bias.csv") %>%
  filter(Include == 1) %>%
  select(-instructions, -other_notes)

es = compute_es(
        d$participant_design, d$x_1,d$x_2, d$x_dif, d$SD_1, d$SD_2,
        d$SD_dif, d$n_1, d$n_2, d$t, d$f, d$d, d$d_var, d$corr,
        d$corr_imputed, d$r, d$study_ID, d$expt_num,
        d$special_cases_measures, d$contrast_sampa)

d = cbind(d, es)

Forest plot

Currently I have 80 effect sizes coded.

res <- rma(yi=d_calc, vi = d_var_calc, data=d,
           slab=paste(short_cite,expt_num), method="REML")
 
### set up forest plot (with 2x2 table counts added; rows argument is used
### to specify exactly in which rows the outcomes will be plotted)
forest(res, 
       xlab="Effect size", mlab="", psize=1)

Developmental plots

d %>%
  filter(instruction_code != "best_match") %>%
  filter(instruction_code != "same_kind") %>%
  mutate(mean_month = mean_age_1/30.43, 
         label_present = as.factor(label_present)) %>%
  ggplot(aes(x = mean_month, y = d_calc,color = label_present)) +
      facet_wrap(~instruction_code, scales = "free") +
      geom_jitter(aes(size = n_1), alpha = 0.5) +
      geom_hline(yintercept = 0, linetype = "dashed", color = "black") +
      xlim(10, 65) +
      scale_size_continuous(guide = FALSE) +
      geom_smooth(method = "lm", aes(group = label_present)) +
      ylab("Effect size (taxonomic bias)") +
      theme_bw()

Difficult to compare effect sizes across tasks directions. For the conditions that we have the same directions for both with and without label (“another”), it looks like there’s a developmental trend of taxonomic bias when children are given a label. But….could this trend just be an artifact of learning the word “another”?

Development of “another” knowledge

Data from Wordbank.

ap = read.csv("another_produces.csv") %>%
  rename(prop_know = another,
         mean_month = age)
au = read.csv("another_understands.csv") %>%
    rename(prop_know = another,
         mean_month = age) 

another = rbind(ap, au)

ggplot(another, 
      aes(x = mean_month, y = prop_know, color = measure)) +
      scale_size_continuous(guide = FALSE) +
      xlim(10, 65) +
      ylim(0,1) +
  ylab("prop kids knowing the word `another` ") +
  geom_smooth(method = "lm") +
  theme_bw()