Helmert code a factor

Helmert coding sets the grand mean as the intercept. Each contrast compares one level with the mean of previous levels.

Usage

contr_code_helmert(fct, levels = NULL, colnames = NULL)

Arguments

fct

the factor to contrast code (or a vector)

levels

the levels of the factor in order

colnames

optional list of column names for the added contrasts

Value

the factor with contrasts set

Examples

df <- sim_design(between = list(pet = c("cat", "dog")), 
                 mu = c(10, 20), plot = FALSE)
df$pet <- contr_code_helmert(df$pet)
lm(y ~ pet, df) %>% broom::tidy()
#> # A tibble: 2 × 5
#>   term        estimate std.error statistic   p.value
#>   <chr>          <dbl>     <dbl>     <dbl>     <dbl>
#> 1 (Intercept)    15.1     0.0731     206.  4.51e-233
#> 2 pet.dog-cat     9.91    0.146       67.8 5.82e-139

df <- sim_design(between = list(pet = c("cat", "dog", "ferret")), 
                 mu = c(2, 4, 9), empirical = TRUE, plot = FALSE)
                 
df$pet <- contr_code_helmert(df$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    0.0577      86.6 8.45e-213
#> 2 pet.dog-cat             2      0.141       14.1 4.53e- 35
#> 3 pet.ferret-cat.dog      6      0.122       49.0 2.56e-144

# reorder the levels to change the comparisons
df$pet <- contr_code_helmert(df$pet, levels = c("dog", "cat", "ferret"))
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    0.0577      86.6 8.45e-213
#> 2 pet.cat-dog            -2      0.141      -14.1 4.53e- 35
#> 3 pet.ferret-dog.cat      6      0.122       49.0 2.56e-144

df$pet <- contr_code_helmert(df$pet, levels = c("ferret", "dog", "cat"))
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    0.0577      86.6 8.45e-213
#> 2 pet.dog-ferret         -5      0.141      -35.4 1.89e-108
#> 3 pet.cat-ferret.dog     -4.5    0.122      -36.7 1.71e-112