Generate null data with null residuals from a model.

Null hypothesis: variable is linear combination of predictors

null_lm(f, method = "rotate", additional = FALSE, ...)

Arguments

f

model specification formula, as defined by lm

method

method for generating null residuals. Built in methods 'rotate', 'perm', 'pboot' and 'boot' are defined by resid_rotate, resid_perm, resid_pboot and resid_boot respectively

additional

whether to compute additional measures: standardized residuals and leverage

...

other arguments passed onto method.

Value

a function that given data generates a null data set. For use with lineup or rorschach

See also

null_permute, null_dist

Examples

data(tips)
x <- lm(tip ~ total_bill, data = tips)
tips.reg <- data.frame(tips, .resid = residuals(x), .fitted = fitted(x))
library(ggplot2)
ggplot(lineup(null_lm(tip ~ total_bill, method = 'rotate'), tips.reg)) +
  geom_point(aes(x = total_bill, y = .resid)) +
  facet_wrap(~ .sample)
#> decrypt("DruT c2V2 AR LeOAVAeR 44")