Use treatment coding — treatment

Wrapper around stats::contr.treatment(). Returns a contrast matrix where comparisons give differences between each comparison level and a baseline reference level, while the intercept equals the first level of the factor. See scaled_sum_code() for a function that centers the intercept on the grand mean while retaining pairwise comparisons from a reference level.

Usage

treatment_code(n)

Arguments

n: Integer umber of factor levels to compute contrasts for.

Value

A contrast matrix with dimensions n rows and (n-1) columns.

Details

For n levels of factors, generate a matrix with n-1 comparisons where:

Reference level = 0
Comparison level = 1
All others = 0

Note that this function sets the first level (alphabetically) as the reference level while stats::contr.SAS() sets the LAST level as the reference level. However, in functions like set_contrasts(), and enlist_contrasts(), the reference level is automatically set to be the first level alphabetically.

Examples

mydf <- data.frame(
  grp = gl(4,5),
  resp = c(seq(1, 5), seq(5, 9), seq(10, 14), seq(15, 19))
)

mydf <- set_contrasts(mydf, grp ~ treatment_code)

lm(resp ~ grp, data = mydf)
#> 
#> Call:
#> lm(formula = resp ~ grp, data = mydf)
#> 
#> Coefficients:
#> (Intercept)         grp2         grp3         grp4  
#>           3            4            9           14  
#>