ggplot2, gt (>= 0.3.0), huxtable, IRdisplay, knitr, lme4,
lmtest, MASS, nnet, officer, rmarkdown, sandwich, testthat,

1.2.1), parameters, performance, rlang, tables
Suggests: AER, broom.mixed, digest, estimatr, flextable, fixest,
gamlss, ggplot2, gt (>= 0.3.0), huxtable, IRdisplay, knitr,
lme4, lmtest, MASS, nnet, officer, rmarkdown, sandwich,

Packaged: 2021-08-12 14:04:51 UTC; vincent-imac

Suggests: AER, betareg, bookdown, broom.mixed, covr, did, digest,
estimatr, fixest, flextable, gamlss, ggplot2, gt (>= 0.3.0),
huxtable, IRdisplay, knitr, ivreg, lfe, lme4, lmtest, magick,
officer, rmarkdown, sandwich, spelling, testthat, MASS, mice,

rmarkdown, sandwich, spelling, testthat, MASS, mice, nnet,

rmarkdown, sandwich, spelling, testthat, tibble, MASS, mice,

correlation matrices. This package supports dozens of statistical models, and
it can produce tables in HTML, LaTeX, Word, Markdown, PDF, PowerPoint, Excel,
RTF, JPG, or PNG. Tables can easily be embedded in 'Rmarkdown' or 'knitr'
dynamic documents. Details can be found in Arel-Bundock (2022)

lmtest, magick, marginaleffects, officer, parallel, rmarkdown,
sandwich, spelling, survey, testthat, tibble, MASS, mice, nnet,

Imports: broom, checkmate (>= 2.1.0), data.table, generics, glue,
insight (>= 0.18.5), kableExtra (>= 1.2.1), parameters (>=
Suggests: betareg, bookdown, broom.mixed, clubSandwich, covr, digest,
DT, estimatr, fixest (> 0.10.3), flextable, future,
future.apply, gamlss, ggplot2, gt (>= 0.3.0), haven, huxtable,
IRdisplay, knitr, lfe, lme4, lmtest, magick, marginaleffects,
MASS, mgcv, mice, nnet, officer, openxlsx, parallel, pscl,
rmarkdown, sandwich, spelling, survey, testthat, tibble,

insight (>= 0.18.7), kableExtra (>= 1.2.1), parameters (>=
MASS, mgcv, mice, nlme, nnet, officer, openxlsx, parallel,
pscl, rmarkdown, sandwich, spelling, survey, testthat, tibble,

Title: Testing Infrastructure for Broom Model Generics
Description: Provides a number of testthat tests that can be
used to verify that tidy(), glance() and augment() methods meet
consistent specifications. This allows methods for the same generic
to be spread across multiple packages, since all of those packages
can make the same guarantees to users about returned objects.
Imports: dplyr (>= 0.7.6), generics, purrr (>= 0.2.5), testthat (>=