Listing of Supported Models

supported_models

Format

A data frame with one row per supported model

model: Model
notes: Notes

Supported models

model	notes
`betareg::betareg()`	Use `tidy_parameters()` as `tidy_fun` with `component` argument to control with coefficients to return. `broom::tidy()` does not support the `exponentiate` argument for betareg models, use `tidy_parameters()` instead.
`biglm::bigglm()`
`biglmm::bigglm()`
`brms::brm()`	`broom.mixed` package required
`cmprsk::crr()`	Limited support. It is recommended to use `tidycmprsk::crr()` instead.
`fixest::feglm()`	May fail with R <= 4.0.
`fixest::femlm()`	May fail with R <= 4.0.
`fixest::feNmlm()`	May fail with R <= 4.0.
`fixest::feols()`	May fail with R <= 4.0.
`gam::gam()`
`geepack::geeglm()`
`glmmTMB::glmmTMB()`	`broom.mixed` package required
`lavaan::lavaan()`	Limited support for categorical variables
`lfe::felm()`
`lme4::glmer.nb()`	`broom.mixed` package required
`lme4::glmer()`	`broom.mixed` package required
`lme4::lmer()`	`broom.mixed` package required
`logitr::logitr()`	Requires logitr >= 0.8.0
`MASS::glm.nb()`
`MASS::polr()`
`mgcv::gam()`	Use default tidier `broom::tidy()` for smooth terms only, or `gtsummary::tidy_gam()` to include parametric terms
`mice::mira`	Limited support. If `mod` is a `mira` object, use `tidy_fun = function(x, ...) {mice::pool(x) %>% mice::tidy(...)}`
`mmrm::mmrm()`
`multgee::nomLORgee()`	Experimental support. Use `tidy_multgee()` as `tidy_fun`.
`multgee::ordLORgee()`	Experimental support. Use `tidy_multgee()` as `tidy_fun`.
`nnet::multinom()`
`ordinal::clm()`	Limited support for models with nominal predictors.
`ordinal::clmm()`	Limited support for models with nominal predictors.
`parsnip::model_fit`	Supported as long as the type of model and the engine is supported.
`plm::plm()`
`pscl::hurdle()`	Use `tidy_zeroinfl()` as `tidy_fun`.
`pscl::zeroinfl()`	Use `tidy_zeroinfl()` as `tidy_fun`.
`rstanarm::stan_glm()`	`broom.mixed` package required
`stats::aov()`	Reference rows are not relevant for such models.
`stats::glm()`
`stats::lm()`
`stats::nls()`	Limited support
`survey::svycoxph()`
`survey::svyglm()`
`survey::svyolr()`
`survival::cch()`	`Experimental support.
`survival::clogit()`
`survival::coxph()`
`survival::survreg()`
`tidycmprsk::crr()`
`VGAM::vglm()`	Limited support. It is recommended to use `tidy_parameters()` as `tidy_fun`.