Log message:
(math/Rinsight) Updated 0.14.4 to 0.17.1
# Insight 0.17.1
## New supported model classes
* `deltaMethod` (*car*), `marginaleffects`, `marginaleffects.summary`
(*marginaleffects*)
## General
* `get_predicted()` now supports models of class `iv_robust` and `ivreg`.
* For `get_predicted()`, when both `type` and `predict` are given, `type`
will overwrite `predict`. Note that this will print a message, because
`predict` is the preferred argument.
* `get_varcov()` gains `vcov` and `vcov_args` arguments, to specify the
variancecovariance matrix used to compute uncertainty estimates (e.g., for
robust standard errors).
* `get_loglikehood()` improved handling of models from package *estimator*.
## Bug fixes
* Fixed bug in `get_data()` for model objects whose data needs to be recovered
from the environment, and where the data name was a reserved word (e.g., named
like an R function).
* The matrix returned by `get_varcov()` for models of class *bife* now returns
row and column names.
* `find_offset()` did not find offsetterms for `merMod` objects when the
offset was specified as `offset` argument in the function call.
# insight 0.17.0
## Breaking changes
* Arguments `vcov_estimation` and `vcov_type` in `get_predicted()`,
`get_predicted_se()` and `get_predicted_ci()` are replaced by `vcov` and
`vcov_args`, to have a more simplified and common interface to control
robust covariance matrix estimation.
## General
* Improved performance for various functions, in particular `get_data()` and
`model_info()`.
## New functions
* To check for names: `object_has_names()` and `object_has_rownames()`
* To work with lists: `is_empty_object()` and `compact_list()`
* To work with strings: `compact_character()`
* Further utility functions are `safe_deparse()`, `trim_ws()` and `n_unique()`.
## Changes to functions
* `export_table()` now better checks for invalid values of caption and footer
for tables in HTML format, and silently removes, e.g., ansicolour codes that
only work for textformat.
* `get_data.coxph()` returns the original data frame instead of data with type
coercion.
* `get_loglikelihood()` gets a `check_response` argument, to check if a model
has a transformed response variable (like `log()` or `sqrt()` transformation),
and if so, returns a corrected loglikelihood.
* `get_modelmatrix()` now supports *BayesFactor* models.
* `get_loglikelihood()` and `get_df()` now support more model classes.
* `get_predicted()` was improved for multinomial models from *brms*.
* `get_variance()` was improved to cover more edge cases of (more complex)
random effect structures.
* `get_data()` now includes variables in the returned data frame that were
used in the `subset` argument of regression functions (like `lm()`).
* In some edge cases, where `get_data()` is unable to retrieve the data that
was used to fit the model, now a more informative error is printed.
* `ellipses_info()` now also accepts a list of model objects, is more stable
and returns more information about the provided models (like if all fixed
or random effects are the same across models, if all models are mixed models
or nullmodels, etc.)
* `check_if_installed()` now works interactively and lets the user prompt
whether to automatically update or install packages.
## Bug fixes
* Fixed incorrect column name conversion in `standardize_names()` for certain
columns returned by `broom::glance()`.
* Fixed issue with correctly detecting Tweediemodels in `model_info()`.
* Fixed issue with `get_datagrid()` for *brms* models with monotonic factors.
* Fixed issue in `find_formula()` when argument `correlation` was defined
outside of `lme()` and `gls()` (@etiennebacher, #525).
* Fixed issue with `get_data()` when backtransforming data from predictors
that used `cos()`, `sin()` or `tan()` transformations.
# insight 0.16.0
## New functions
* `get_datagrid()`, to generate a reference grid, usually used when computing
adjusted predictions or marginal means from regression models.
## Changes to functions
### `get_predicted()`
* `get_predicted()` was revised. Beside the four core options for the `predict`
argument, it is now also possible to use any value that is valid for the
model's `predict()` method's `type` argument.
* `get_predicted()` now supports more models (e.g., from packages like
_GLMMadaptive_ or _survival_).
* `get_predicted()` is now more robust when calculating standard errors of
predictions.
### Other functions
* `get_statistic()` and `find_statistic()` now support *htest* objects.
## General
* Various minor improvements.
# insight 0.15.1
## General
* Improved speed performance, especially for `get_data()`.
## Changes to functions
* `get_data()` for `coxph` models now returns the original factor levels for
variables transformed with `strata()` inside formulas.
# insight 0.15.0
## Breaking changes
* Data management functions (like `reshape_longer()`, or `data_match()`) have
been moved to the *datawizard* package.
* `get_data()` no longer returns factor types for numeric variables that have
been converted to factors onthefly within formulas (like `y ~ as.factor(x)`).
Instead, for each numeric variable that was coerced to factor within a formula
gets a `factor` attribute (set to `TRUE`), and the returned data frame gets
a `factors` attribute including all names of affected variables.
## New supported model classes
* Support for `bfsl` (*bfsl*)
## New functions
* New `standardize_column_order()` function can be used to standardize the
column order in output dataframes.
## General
* Improved speed performance for some functions.
* Improved handling of table captions and footers in `export_table()`. See also
the new vignette on exporting data frames into human readable tables here:
https://easystats.github.io/insight/articles/export.html
* Revised `width` argument in `export_table()`, which now allows to set
different column widths across table columns. See examples in
`?export_table`.
* `export_table()` gets a `table_width` argument to split wide tables into
two parts.
* `get_varcov()` for `MixMod` (package *GLMMadaptive*) was revised, and now
allows to return a robust variancecovariance matrix.
* Added more `get_df()` methods.
## Bug fixes
* Fixed issues with manual sigma computation to handle dispersion models in
`get_sigma()`.
* Fixed issue in `find_formula()` for `BayesFactor::lmBF()` with multiple random
effects.
* Fixed issue in `get_parameters.BFBayesFactor()` with wrong sign of difference
estimate for ttests.
* Argument `width` in `format_value()` was ignored when formatting integer
values and `protect_integers` was set to `TRUE`.
# insight 0.14.5
## New functions
* `find_transformation()` and `get_transformation()` to find or get any function
that was used to transform the response variable in a regression model.
## General
* Improved support for models of class `sampleSelection`.
* Improved documentation.
* `get_modelmatrix()` now supports: `rms::lrm`
* `get_predicted()` supports: `MASS::polr`, `MASS::rlm`, `rms::lrm`, `fixest`,
`bife::bife`, `ordinal::clm`.
* `get_predicted()` standard errors are often much faster to compute.
* `get_predicted()` supports models with "grouped" or \
"level" outcomes (e.g.,
multinomial logit).
* `get_predicted()` handles factors better.
* Improved documentation
## Changes to functions
* `check_if_installed()` gains a `quietly` argument, if neither stopping nor a
warning message for noninstalled packages is requested.
* `get_predicted()`'s `predict` argument now accepts these values: "link",
"expectation", "prediction", "classification", \
or NULL.
* `get_predicted()` accepts `predict=NULL`, which allows users to push a `type`
argument through the `...` ellipsis, forward to the `predict()` method of the
modelling package.
## Bug fixes
* Fixed issue with parameter names from *emmeans* objects in
`get_parameters()`.
* Fixed issues with unknown arguments in `get_predicted()`.

Log message:
(math/Rinsight) import Rinsight0.14.4
A tool to provide an easy, intuitive and consistent access to
information contained in various R models, like model formulas, model
terms, information about random effects, data that was used to fit the
model or data from response variables. 'insight' mainly revolves
around two types of functions: Functions that find (the names of)
information, starting with 'find_', and functions that get the
underlying data, starting with 'get_'. The package has a consistent
syntax and works with many different model objects, where otherwise
functions to access these information are missing.
