tibble 3.0.0 release. Removed xergm dependency.Fixes failing CRAN checks
Changes to accomodate ergm 3.10 release. tidy.ergm() no longer has a quick argument. The old default of quick = FALSE is now the only option.
tidy(), glance() and augment() are now re-exported from the generics package.Tidiers now return tibble::tibble()s. This release also includes several new tidiers, new vignettes and a large number of bugfixes. We’ve also begun to more rigorously define tidier specifications: we’ve laid part of the groundwork for stricter and more consistent tidying, but the new tidier specifications are not yet complete. These will appear in the next release.
Additionally, users should note that we are in the process of migrating tidying methods for mixed models and Bayesian models to broom.mixed. broom.mixed is not on CRAN yet, but all mixed model and Bayesian tidiers will be deprecated once broom.mixed is on CRAN. No further development of mixed model tidiers will take place in broom.
Almost all tidiers should now return tibbles rather than data.frames. Deprecated tidying methods, Bayesian and mixed model tidiers still return data.frames.
Users are mostly to experience issues when using augment in situations where tibbles are stricter than data frames. For example, specifying model covariates as a matrix object will now error:
library(broom)
library(quantreg)
fit <- rq(stack.loss ~ stack.x, tau = .5)
broom::augment(fit)
#> Error: Column `stack.x` must be a 1d atomic vector or a listThis is because the default data argument data = model.frame(fit) cannot be coerced to tibble.
Another consequence of this is that augment.survreg and augment.coxph from the survival package now require that the user explicitly passes data to either the data or newdata arguments.
These restrictions will be relaxed in an upcoming release of broom pending support for matrix-columns in tibbles.
Developers are likely to experience issues:
[, which returns a tibble rather than a vector.tbl_df and tbl beyond the data.frame classroxygen2 template based documentation system.This version of broom includes several new vignettes:
vignette("available-methods", package = "broom") contains a table detailing which tidying methods are availablevignette("adding-tidiers", package = "broom") is an in-progress guide for contributors on how to add new tidiers to broomvignette("glossary", package = "broom") contains tables describing acceptable argument names and column names for the in-progress new specification.Several old vignettes have also been updated:
vignette("bootstrapping", package = "broom") now relies on the rsample package and a tidyr::nest-purrr::map-tidyr::unnest workflow. This is now the recommended workflow for working with multiple models, as opposed to the old dplyr::rowwise-dplyr::do based workflow.tibble::as_tibble and tibble::enframebootstrap() has been deprecated in favor of the rsampleinflate has been removed from broomalpha argument has been removed from quantreg tidy methodsseparate.levels argument has been removed from tidy.TukeyHSD. To obtain the effect of separate.levels = TRUE, users may tidyr::separate after tidying. This is consistent with the multcomp tidier behavior.fe.error argument was removed from tidy.felm. When fixed effects are tidier, their standard errors are now always included.diag argument in tidy.dist has been renamed diagonalglance support for arima objects fit with method = "CSS" (#396 by @josue-rodriguez)glmnet objects with family = multinomial (#395 by @erleholgersen)quantreg intercept only models (#378 by @erleholgersen)aovlist objects (#377 by @mvevans89)glmnetUtils objects (#352 by @Hong-Revo)tidy_emmeans to handle column names with dashes (#351 by @bmannakee)augment.felm no longer returns .fe_ and .comp columnsaugment.felm (#347 by @ShreyasSingh)confint_tidy now drops rows of all NA (#345 by @atyre2)caret::confusionMatrix objects (#344 by @mkuehn10)Kendall::Kendall objects (#343 by @cimentadaj)car::durbinWatsonTest objects (#341 by @mkuehn10)glance throws an informative error for quantreg:rq models fit with multiple tau values (#338 by @bfgray3)tidy.glmnet gains the ability to retain zero-valued coefficients with a return_zeros argument that defaults to FALSE (#337 by @bfgray3)tidy.manova now retains a Residuals row (#334 by @jarvisc1)ordinal::clm, ordinal::clmm, survey::svyolr and MASS::polr ordinal model objects (#332 by @larmarange)anova objects from car::Anova (#325 by @mariusbarth)tseries::garch models (#323 by @wilsonfreitas)psych package (#313 by @nutterb)rstanarm and loo packages (#298 by @jgabry)irlba::irlbatidy.prcomp when missing labels (#265 by @corybrunson)pkgdown site at https://broom.tidyverse.org/ (#260 by @jayhesselberth)AER::ivreg models (#247 by @hughjonesd)lavaan package (#233 by @puterleat)conf.int argument to tidy.coxph (#220 by @larmarange)augment method for chi-squared tests (#138 by @larmarange)Many many thanks to all the following for their thoughtful comments on design, bug reports and PRs! The community of broom contributors has been kind, supportive and insighftul and I look forward to working you all again!
[@atyre2](https://github.com/atyre2), [@batpigandme](https://github.com/batpigandme), [@bfgray3](https://github.com/bfgray3), [@bmannakee](https://github.com/bmannakee), [@briatte](https://github.com/briatte), [@cawoodjm](https://github.com/cawoodjm), [@cimentadaj](https://github.com/cimentadaj), [@dan87134](https://github.com/dan87134), [@dgrtwo](https://github.com/dgrtwo), [@dmenne](https://github.com/dmenne), [@ekatko1](https://github.com/ekatko1), [@ellessenne](https://github.com/ellessenne), [@erleholgersen](https://github.com/erleholgersen), [@Hong-Revo](https://github.com/Hong-Revo), [@huftis](https://github.com/huftis), [@IndrajeetPatil](https://github.com/IndrajeetPatil), [@jacob-long](https://github.com/jacob-long), [@jarvisc1](https://github.com/jarvisc1), [@jenzopr](https://github.com/jenzopr), [@jgabry](https://github.com/jgabry), [@jimhester](https://github.com/jimhester), [@josue-rodriguez](https://github.com/josue-rodriguez), [@karldw](https://github.com/karldw), [@kfeilich](https://github.com/kfeilich), [@larmarange](https://github.com/larmarange), [@lboller](https://github.com/lboller), [@mariusbarth](https://github.com/mariusbarth), [@michaelweylandt](https://github.com/michaelweylandt), [@mine-cetinkaya-rundel](https://github.com/mine-cetinkaya-rundel), [@mkuehn10](https://github.com/mkuehn10), [@mvevans89](https://github.com/mvevans89), [@nutterb](https://github.com/nutterb), [@ShreyasSingh](https://github.com/ShreyasSingh), [@stephlocke](https://github.com/stephlocke), [@strengejacke](https://github.com/strengejacke), [@topepo](https://github.com/topepo), [@willbowditch](https://github.com/willbowditch), [@WillemSleegers](https://github.com/WillemSleegers), and [@wilsonfreitas](https://github.com/wilsonfreitas)
dplyr::failwith to purrr::possiblyaugment and glance on NULLs now return an empty data frameinflate() function in favor of tidyr::crossingquick = TRUE to return terms as character rather than factor (thanks to #191 from Matteo Sostero)ivreg objects from the AER package (thanks to #245 from David Hugh-Jones)survdiff objects from the survival package (thanks to #147 from Michał Bojanowski)emmeans from the emmeans package (thanks to #252 from Matthew Kay)speedlm and speedglm from the speedglm package (thanks to #248 from David Hugh-Jones)muhaz objects from the muhaz package (thanks to #251 from Andreas Bender)decompose and stl objects from stats (thanks to #165 from Aaron Jacobs)lsmobj and ref.grid objects from the lsmeans packagebetareg objects from the betareg packagelmRob and glmRob objects from the robust packagebrms objects from the brms package (thanks to #149 from Paul Buerkner)tidy.glmnet to filter out rows where estimate == 0.rstanarm tidiers (thanks to #177 from Jonah Gabry)tidy.TukeyHSD to include term column. Also added separate.levels argument, with option to separate comparison into level1 and level2tidy.manova to use correct column name for test (previously, always pillai)kde_tidiers to tidy kernel density estimatesorcutt_tidiers to tidy the results of cochrane.orcutt orcutt packagetidy.dist to tidy the distance matrix output of dist from the stats packagetidy and glance for lmodel2 objects from the lmodel2 packagepoLCA objects from the poLCA packageprcomp objectsMclust objects from the Mclust packageacf objectstidy methods for lists, including u, d, v lists from svd, and x, y, z lists used by image and perspquick argument to tidy.lm, tidy.nls, and tidy.biglm, to create a smaller and faster version of the output.rowwise_df_tidiers to allow the original data to be saved as a list column, then provided as a column name to augment. This required removing data from the augment S3 signature. Also added tests-rowwise.Rtidy.coeftest for coeftest objects from the lmtest package.tidy.lm to work with “mlm” (multiple linear model) objects (those with multiple response columns).tidy and glance for “biglm” and “bigglm” objects from the biglm package.tidy.coxph when one-row matrices are returnedtidy.power.htesttidy and glance for summaryDefault objectstidy and glance for multinom objects from the nnet package.tidy.pairwise.htest, which now can handle cases where the grouping variable is numeric.tidy.aovlist method. This added stringr package to IMPORTS to trim whitespace from the beginning and end of the term and stratum columns. This also required adjusting tidy.aov so that it could handle strata that are missing p-values.glance.lm to work with aov objects along with lm objects.tidy and glance for matrix objects, with tidy.matrix converting a matrix to a data frame with rownames included, and glance.matrix returning the same result as glance.data.frame.felm where the .fitted and .resid columns were matrices rather than vectors.rlm (robust linear model) and gam (generalized additive model) objects, including adjustments to “lm” tidiers in order to handle them. See ?rlm_tidiers and ?gam_tidiers for more.tidy.cv.glmnet outputThe behavior of augment, particularly with regard to missing data and the na.exclude argument, has through the use of the augment_columns function been made consistent across the following models:
lmglmnlsmerMod (lme4)survreg (survival)coxph (survival)Unit tests in tests/testthat/test-augment.R were added to ensure consistency across these models.
tidy, augment and glance methods were added for rowwise_df objects, and are set up to apply across their rows. This allows for simple patterns such as:
regressions <- mtcars %>% group_by(cyl) %>% do(mod = lm(mpg ~ wt, .))
regressions %>% tidy(mod)
regressions %>% augment(mod)See ?rowwise_df_tidiers for more.
Added tidy and glance methods for Arima objects, and tidy for pairwise.htest objects.
Fixes for CRAN: change package description to title case, removed NOTES, mostly by adding globals.R to declare global variables.
This is the original version published on CRAN.
lme4glmnetsurvivalzoofelmMASS (ridgelm objects)tidy and glance methods for data.frames have also been added, and augment.data.frame produces an error (rather than returning the same data.frame).stderror has been changed to std.error (affects many functions) to be consistent with broom’s naming conventions for columns.bootstrap has been added based on this example, to perform the common use case of bootstrapping models.