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Use sum coding

Source: R/contrasts_sum.R
sum_code.Rd

Same as contr.sum, but ensures that the reference level is the first level alphabetically, not the last. Returns a contrast matrix where comparisons give differences between comparison levels and the grand mean.

Usage

sum_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 = -1

  • Comparison level = 1

  • All others = 0

Example interpretation for a 4 level factor:

  • Intercept = Grand mean (mean of the means of each level)

  • grp2 = grp2 - mean(grp4, grp3, grp2, grp1)

  • grp3 = grp3 - mean(grp4, grp3, grp2, grp1)

  • grp4 = grp4 - mean(grp4, grp3, grp2, grp1)

Note that when n = 2, the coefficient estimate is half of the difference between the two levels. But, this coincidence does not hold when the number of levels is greater than 2.

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 ~ sum_code)

lm(resp ~ grp, data = mydf)
#> 
#> Call:
#> lm(formula = resp ~ grp, data = mydf)
#> 
#> Coefficients:
#> (Intercept)         grp2         grp3         grp4  
#>        9.75        -2.75         2.25         7.25  
#>