Comments (3)
I love this. For now, these functions have only worked with tbl_summary()
, and I have wanted to generalize them for tbl_regression()
. We should implement something like this! Just need to decide on the best route!
The possible types would be continuous, categorical, dichotomous, interaction, and unknown (for when there is no model.frame()
method)? We should probably implement selectors for all types (well, except known)?
all_continuous()
all_categorical(dichotomous = TRUE)
all_dichotomous()
all_interaction()
I can implement the same in gtsummary, but I am not sure I'll be able to merely reexport the broom.helper functions if I want them to work with all the gtsummary obejcts. For example, we also have a summary type called continuous2
that has it's own selector. There is likely a pretty straightforward way around the issue...just need to sit with it longer and think :)
from broom.helpers.
Sure, we should think properly how to implement it.
If I understood properly, your trick in broom::.tidy_tidyselect()
, you recreate a tibble (df_empty
) with the list of variables to be able to apply dplyr::select()
.
I guess you use something similar in gt_summary
.
Maybe a possible trick could be to add a "var_type" attribute to each column of df_empty
. Then, to create functions as is_continous()
, is_categorical()
who test the value of the attribute, and finaly to code all_categorical()
as a where(is_categorical)
?
Just brainstorming...
Just some clarifications: what is exactly the type continuous2
?
Regards
from broom.helpers.
continuous2
variables are those that are summarized on 2 or more rows in tbl_summary()
and tbl_svysummary()
.
trial %>%
select(age, trt) %>%
tbl_summary(
by = trt,
type = all_continuous() ~ "continuous2",
statistic = all_continuous() ~ c("{N_nonmiss}",
"{mean} ({sd})",
"{median} ({p25}, {p75})"),
missing = "no"
)
from broom.helpers.
Related Issues (20)
- Support with coxphf model HOT 9
- Bug fixes and improvements for mixed models HOT 1
- tbl_regression (package gtsummary) and ggcoef_model (package ggstats) not working on the output of a replicate svyglm model HOT 2
- fantastic support of multivariate quantile regression for any quantile HOT 1
- Support for survival::cch model? HOT 5
- Avg_comparisons and nlme::lme() models HOT 1
- order of variable levels with marginal tidiers HOT 8
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- `marginaleffects::datagridcf()` is deprecated
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- Explore better support of VGAM::vglm() models HOT 1
- Execution time HOT 4
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- Speed improvement when _parameters_ package is used HOT 2
- `tidy_multgee` Incorrectly Defines Values in `y.levels` for Nominal Logistic Regression HOT 1
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- Check if variable labels are passed for a polynomial continuous terms HOT 1
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