fit_average_estimates.r

fit %>% 
  filter(term != "(Intercept)") %>% 
  group_by(term) %>% 
  summarise(estimate = mean(estimate), 
            conf.low = mean(conf.low), 
            conf.high = mean(conf.high), 
            sig_0005 = ifelse(sum(sig_0005) > 6, "significant (< 0.005)", "not significant")) %>% 
  ggplot(aes(y = reorder(term, estimate), x = estimate, colour = sig_0005)) +
  geom_point() + 
  geom_errorbarh(aes(xmax = conf.high, xmin = conf.low)) +
  theme_minimal() +
  geom_vline(aes(xintercept = 0), linetype = "dashed", colour = "blue") +
  labs(title = "Linear regression estimates", 
       subtitle = "Dependent variable: IMDB score", 
       x = "Independent variable", 
       y = "estimate")