Predictions

B0 <- tidy_summary_1$estimate[1]
B1 <- tidy_summary_1$estimate[2]
B2 <- tidy_summary_1$estimate[3]
d %>%
  add_fitted_draws(model2, n = 200, re_formula = NA) %>%
  ggplot(aes(x = ADF, y = ADG)) +
  geom_line(aes(y = .value, group = .draw), alpha = 0.1) +
  geom_abline(intercept = B0+B2, slope = B1, color = "blue") +theme_bw()

Studycode_summaries_1 <- model2 %>%
  spread_draws(`(Intercept)`, b[,Studycode]) %>% 
  mutate(Studycode_intercept = `(Intercept)` + b) %>% 
  dplyr::select(-`(Intercept)`, -b) %>% 
  median_qi(.width = 0.80) %>% 
  dplyr::select(Studycode, Studycode_intercept, .lower, .upper)
Studycode_summaries_1  %>% 
  filter(Studycode %in% c("Studycode:V0011207", "Studycode:V0011270"))

d %>%
  filter(Studycode %in% c("V0011207", "V0011270")) %>% 
  add_fitted_draws(model2, n = 100) %>%
  ggplot(aes(x = ADF, 
             y = ADG)) +
  geom_line(
    aes(y = .value, 
        group = paste(Studycode, .draw), 
        color = Studycode),
    alpha = 0.1) +
  geom_point(aes(color = Studycode)) + theme_bw()