Comments (3)
strengejacke
commented on May 27, 2024
What about this?
mtcars |>
datawizard::data_modify(grp = cut(mpg, breaks = c(0, 15, 20, 50))) |>
lm(wt ~ grp, data = _) |>
parameters::parameters()
#> Parameter | Coefficient | SE | 95% CI | t(29) | p
#> -------------------------------------------------------------------
#> (Intercept) | 4.50 | 0.24 | [ 4.01, 4.99] | 18.91 | < .001
#> grp [>15-20] | -0.99 | 0.29 | [-1.59, -0.40] | -3.40 | 0.002
#> grp [>20-50] | -2.08 | 0.28 | [-2.66, -1.50] | -7.32 | < .001
#>
#> Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
#> using a Wald t-distribution approximation.Created on 2024-02-06 with reprex v2.1.0
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bwiernik
commented on May 27, 2024
That looks good to me, and it's easier to understand than the distinction between [ and ( ranges.
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snhansen
commented on May 27, 2024
Yes, this is great. I like the solution.
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