read the per-axis report off a combined score

[score_multi()] records which axes it screened and what it found, so the contribution of each attribute can be checked after the fact rather than having to be re-derived from the inputs.

Usage

axis_report(scores)

Arguments

scores

a score table produced by [score_multi()] or [score_by_knowledge()]

Value

the "reid_axis_report" data frame attached to `scores`, or NULL when the score was produced with `screen = "none"` or did not come from [score_multi()]

Examples

d <- create_dummy_qi_data(people = 40, seed = 1)
j <- join_raw_anon_data(d, d)
axis_report(score_multi(j, c(AGE = "num", SEX = "char")))
#> axis informativeness (2 axis/axes, alpha = 0.05)
#>   AGE                  success 0.8000  baseline 0.0250  lift  32.00x  rank 0.033  z  10.53  p = 0.0000  informative
#>   SEX                  success 0.0500  baseline 0.0250  lift   2.00x  rank 0.265  z   6.29  p = 0.0000  informative