19.11 Posterior summaries

• The two models lead to similar conclusions for the relationship with age and oxygen use.

# Get trend summaries for both models
climb_model_1_mean <- tidy(climb_model_1, effects = "fixed")
climb_model_2_mean <- tidy(climb_model_2, effects = "fixed")

# Combine the summaries for both models
climb_model_1_mean %>%
  right_join(., climb_model_2_mean, by ="term",
             suffix = c("_model_1", "_model_2")) %>%
  select(-starts_with("std.error"))

  term            estimate_model_1 estimate_model_2
  <chr>                      <dbl>            <dbl>
1 (Intercept)              -1.41            -1.53  
2 age                      -0.0475          -0.0474
3 oxygen_usedTRUE           5.79             6.18  

• Different accounting of the variability in success rates.

  term                         estimate_model_1 estimate_model_2
  <chr>                                   <dbl>            <dbl>
1 sd_(Intercept).expedition_id             3.63             3.09
2 sd_(Intercept).peak_name                NA                1.85

• This makes sense, not only are some expeditions more successeful , some peaks are easier to climb.