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The problem
I'm having trouble with getting the residual values when we transform the variable. Usually the tibble has 9 columns but for the log transformation, it just provides 8. This issue is not present when the variable is pre-transformed.
Reproducible example
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reprex::reprex(si = TRUE)
library(reprex)
library(alr4)
#> Loading required package: car
#> Loading required package: carData
#> Loading required package: effects
#> Registered S3 methods overwritten by 'lme4':
#> method from
#> cooks.distance.influence.merMod car
#> influence.merMod car
#> dfbeta.influence.merMod car
#> dfbetas.influence.merMod car
#> lattice theme set by effectsTheme()
#> See ?effectsTheme for details.
library(broom)
modelUN <- lm(I(log(fertility)) ~ I(log(ppgdp)), data = UN11)
augment(modelUN)
#> # A tibble: 199 x 8
#> .rownames `I(log(fertilit~ `I(log(ppgdp))` .fitted .std.resid .hat .sigma
#> <chr> <I<dbl>> <I<dbl>> <dbl> <I<dbl>> <dbl> <dbl>
#> 1 Afghanis~ 1.79 6.21 1.38 1.34 0.0156 0.306
#> 2 Albania 0.422 8.21 0.965 -1.77 0.00516 0.305
#> 3 Algeria 0.762 8.41 0.924 -0.530 0.00503 0.308
#> 4 Angola 1.64 8.37 0.931 2.30 0.00504 0.304
#> 5 Anguilla 0.693 9.53 0.692 0.00500 0.00739 0.308
#> 6 Argentina 0.776 9.12 0.776 -0.000217 0.00593 0.308
#> 7 Armenia 0.551 8.02 1.00 -1.48 0.00544 0.306
#> 8 Aruba 0.513 10.0 0.586 -0.239 0.0102 0.308
#> 9 Australia 0.667 11.0 0.397 0.889 0.0179 0.307
#> 10 Austria 0.297 10.7 0.445 -0.486 0.0156 0.308
#> # ... with 189 more rows, and 1 more variable: .cooksd <I<dbl>>
Created on 2020-10-08 by the reprex package (v0.3.0)
When you are ready to file the bug 🐛 report, please delete everything above this line:
< -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -->
The problem
I'm having trouble with getting the residual values when we transform the variable. Usually the tibble has 9 columns but for the log transformation, it just provides 8. This issue is not present when the variable is pre-transformed.
Reproducible example
Created on 2020-10-08 by the reprex package (v0.3.0)