[Rd] as.data.frame() methods for model objects

[Martin Maechler]

>>>>> SOEIRO Thomas via R-devel 
>>>>>     on Fri, 17 Jan 2025 14:19:31 +0000 writes:

> Following Duncan Murdoch's off-list comments (thanks again!), here is a more complete/flexible version:
> 
> as.data.frame.lm <- function(x, ..., level = 0.95, exp = FALSE) {
>   cf <- x |> summary() |> stats::coef()
>   ci <- stats::confint(x, level = level)
>   if (exp) {
>     cf[, "Estimate"] <- exp(cf[, "Estimate"])
>     ci <- exp(ci)
>   }
>   df <- data.frame(row.names(cf), cf, ci, row.names = NULL)
>   names(df) <- c("term", "estimate", "std.error", "statistic", "p.value", "conf.low", "conf.high")
>   df
> }

Indeed, using level is much better already.

Instead of the  exp = FALSE ,
I'd use    transFUN = NULL
and then

    if(!is.null(transFUN)) {
       stopifnot(is.function(transFUN))
       cf[, "Estimate"] <- transFUN(cf[, "Estimate"])
       ci <- transFUN(ci)
    }

Noting that I'd want "inverse-logit" (*) in some cases, but also
different things for different link functions, hence just
exp = T/F  is not enough.

Martin

--
*) "inverse-logit"  is simply R's   plogis()  function;  quite a
 few people have been re-inventing it, also in their packages ...



> > lm(breaks ~ wool + tension, warpbreaks) |> as.data.frame()
>          term   estimate std.error statistic      p.value  conf.low  conf.high
> 1 (Intercept)  39.277778  3.161783 12.422667 6.681866e-17  32.92715 45.6284061
> 2       woolB  -5.777778  3.161783 -1.827380 7.361367e-02 -12.12841  0.5728505
> 3    tensionM -10.000000  3.872378 -2.582393 1.278683e-02 -17.77790 -2.2221006
> 4    tensionH -14.722222  3.872378 -3.801856 3.913842e-04 -22.50012 -6.9443228
> 
> > glm(breaks < 20 ~ wool + tension, data = warpbreaks) |> as.data.frame(exp = TRUE)
> Waiting for profiling to be done...
>          term estimate std.error statistic    p.value  conf.low conf.high
> 1 (Intercept) 1.076887 0.1226144 0.6041221 0.54849393 0.8468381  1.369429
> 2       woolB 1.076887 0.1226144 0.6041221 0.54849393 0.8468381  1.369429
> 3    tensionM 1.248849 0.1501714 1.4797909 0.14520270 0.9304302  1.676239
> 4    tensionH 1.395612 0.1501714 2.2196863 0.03100435 1.0397735  1.873229
> 
> Thank you.
> 
> Best regards,
> Thomas
> 
> 
> 
> -----Message d'origine-----
> De : SOEIRO Thomas 
> Envoyé : jeudi 16 janvier 2025 14:36
> À : r-devel using r-project.org
> Objet : as.data.frame() methods for model objects
> 
> 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