Dear Stackoverflow community,
I am struggling with using the tidy function from the broom package. I need this function in the context of a multiple imputation.
You can see here a reprex example using a ggplot2 dataset.
library(ggplot2, quietly = T)
library(AER, quietly = T)
#>
#> Attaching package: 'zoo'
#> The following objects are masked from 'package:base':
#>
#> as.Date, as.Date.numeric
library(broom, quietly = T)
library(tidyverse, quietly = T)
data <- ggplot2::diamonds
data
#> # A tibble: 53,940 × 10
#> carat cut color clarity depth table price x y z
#> <dbl> <ord> <ord> <ord> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
#> 1 0.23 Ideal E SI2 61.5 55 326 3.95 3.98 2.43
#> 2 0.21 Premium E SI1 59.8 61 326 3.89 3.84 2.31
#> 3 0.23 Good E VS1 56.9 65 327 4.05 4.07 2.31
#> 4 0.29 Premium I VS2 62.4 58 334 4.2 4.23 2.63
#> 5 0.31 Good J SI2 63.3 58 335 4.34 4.35 2.75
#> 6 0.24 Very Good J VVS2 62.8 57 336 3.94 3.96 2.48
#> 7 0.24 Very Good I VVS1 62.3 57 336 3.95 3.98 2.47
#> 8 0.26 Very Good H SI1 61.9 55 337 4.07 4.11 2.53
#> 9 0.22 Fair E VS2 65.1 61 337 3.87 3.78 2.49
#> 10 0.23 Very Good H VS1 59.4 61 338 4 4.05 2.39
#> # ℹ 53,930 more rows
fit <- AER::tobit(
formula = price ~ z,
left = 500,
right = 1500,
data = data
)
fit %>% summary(tidy)
#> Error in if (correlation) cov2cor(vcov.) else NULL: argument is not interpretable as logical
Created on 2023-07-26 with reprex v2.0.2
I checked my R version and the package version:
R version 4.3.1 (2023-06-16 ucrt) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 19044)
other attached packages: [1] reprex_2.0.2 broom_1.0.5 AER_1.2-10
I identified the following issue and resolution on GitHub but I was not able to transfer it into my in-working project: https://github.com/tidymodels/broom/issues/749 https://github.com/tidymodels/broom/commit/56437bce30841211bfa64074677fe2d9124d99cc
Any help would be very much appreciated!
Thank you in advance!
I came up with a workaround, which you should use with caution: class(fit) is c("tobit", "survreg"), and there is a tidy method for survreg objects (see methods("tidy")), but tidy(fit) returns
Error: No tidy method for objects of class tobit
So:
tidy.tobit <- function(x, ...) {
class(x) <- "survreg"
tidy(x, ...)
}
tidy(fit)
# A tibble: 3 × 5
term estimate std.error statistic p.value
<chr> <dbl> <dbl> <dbl> <dbl>
1 (Intercept) -3109. 19.7 -158. 0
2 z 1420. 6.75 210. 0
3 Log(scale) 5.63 0.00551 1021. 0
This appears to match the results of summary():
summary(fit)
Call:
AER::tobit(formula = price ~ z, left = 500, right = 1500, data = data)
Observations:
Total Left-censored Uncensored Right-censored
53940 1749 18261 33930
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -3.109e+03 1.970e+01 -157.8 <2e-16 ***
z 1.420e+03 6.751e+00 210.3 <2e-16 ***
Log(scale) 5.626e+00 5.511e-03 1020.9 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Scale: 277.6
Gaussian distribution
Number of Newton-Raphson Iterations: 8
Log-likelihood: -1.35e+05 on 3 Df
Wald-statistic: 4.423e+04 on 1 Df, p-value: < 2.22e-16
Note: to make this work in mice you have to explicitly override the version in broom via
assignInNamespace("tidy.tobit",tidy.tobit,ns="broom")
before you run pool().