Hello all,
Would there be any interest for adding as.data.frame() methods for model
objects?
Of course there is packages (e.g. broom), but I think providing methods would
be more discoverable (and the patch would be small).
It is really useful for exporting model results or for plotting.
e.g.:
as.data.frame.lm <- function(x) { # could get other arguments, e.g. exp =
TRUE/FALSE to exponentiate estimate, conf.low, conf.high
cf <- x |> summary() |> stats::coef()
ci <- stats::confint(x)
data.frame(
term = row.names(cf),
estimate = cf[, "Estimate"],
p.value = cf[, 4], # magic number because name changes between lm() and
glm(*, family = *)
conf.low = ci[, "2.5 %"],
conf.high = ci[, "97.5 %"],
row.names = NULL
)
}
> lm(breaks ~ wool + tension, warpbreaks) |> as.data.frame()
term estimate p.value conf.low conf.high
1 (Intercept) 39.277778 6.681866e-17 32.92715 45.6284061
2 woolB -5.777778 7.361367e-02 -12.12841 0.5728505
3 tensionM -10.000000 1.278683e-02 -17.77790 -2.2221006
4 tensionH -14.722222 3.913842e-04 -22.50012 -6.9443228
> glm(breaks < 20 ~ wool + tension, data = warpbreaks) |> as.data.frame()
Waiting for profiling to be done...
term estimate p.value conf.low conf.high
1 (Intercept) 0.07407407 0.54849393 -0.16624575 0.3143939
2 woolB 0.07407407 0.54849393 -0.16624575 0.3143939
3 tensionM 0.22222222 0.14520270 -0.07210825 0.5165527
4 tensionH 0.33333333 0.03100435 0.03900286 0.6276638
Thank you.
Best regards,
Thomas
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