Difference coding sets the grand mean as the intercept. Each contrast compares one level with the previous level.
contr_code_difference(fct, levels = NULL)the factor to contrast code (or a vector)
the levels of the factor in order
the factor with contrasts set
df <- sim_design(between = list(pet = c("cat", "dog", "ferret")),
mu = c(2, 4, 9), empirical = TRUE, plot = FALSE)
df$pet <- contr_code_difference(df$pet)
lm(y ~ pet, df) %>% broom::tidy()
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept) 5 0.0577 86.6 8.45e-213
#> 2 pet.dog-cat 2.00 0.141 14.1 4.53e- 35
#> 3 pet.ferret-dog 5.0 0.141 35.4 1.89e-108