insight 1.4.4

Bug fixes

• Fixed issue with is_converged() due to changes in lme4 package.

• Fixed issue in get_data(source = "mf") for models from package fixest
  when lean was set to TRUE in the model call.

insight 1.4.3

Changes

• Added support for models from package lcmm (lcmm, externVar).

• Support for objects from the modelbased package. This includes methods for
  get_parameters(), get_statistic(), get_df(), get_varcov(),
  find_formula(), find_parameters(), find_statistic(), and get_call().

• Better formatting for p-values-columns from equivalence tests from other
  packages.

• format_value(), format_number(), and export_table() gain a big_mark
  argument to format numbers with thousands separators (e.g., 1,234,567.89 or
  1 234 567.89). This makes large numbers more readable in tables and formatted
  output. When big_mark is provided, scientific notation is suppressed for
  large numbers to show the full value with separators.

• Improved support for models from package survey. This includes a dedicated
  source argument for methods such as get_data(), get_weights(),
  find_weights(), or get_response(), to specify whether the data should be
  extracted from the model frame of the survey design object ("mf"), which is
  usually equivalent to the original data, or from the data that can be extracted
  from the model-object in the environment ("environment") , which usually
  includes processed variables (like the "(weights)" variable for weights).

• get_df() now supports Kenward-Roger and Satterthwaite degrees of freedom
  for models from package glmmTMB. This requires package version 1.1.3.

Bug fixes

• Fix CRAN check failures.

• Fixed issue in get_data() for models from package survey.

• Fixed issue in get_modelmatrix() when the data argument was provided
  and contained columns with only missing values.

insight 1.4.2

Bug fixes

• Fix CRAN failures for Mac OS R-old-release.

insight 1.4.1

Changes

• get_varcov() now supports robust variance-covariance matrices for models
  of class glmmTMB (package glmmTMB). The argument vcov can be used to
  specify the robust variance-covariance matrix function. Furthermore, the
  component argument gains the "full" option, to return the full
  variance-covariance matrix, including the random effects (theta parameters).

• format_table() now also formats ROPE columns for superiority and inferiority.

• format_table() protects integer columns for non-specific column types.

• The numerics argument in get_datagrid() gains two new options, "integer"
  and "mode", to either return the rounded mean or the most frequent value of
  a numeric vector.

• Modified code base to address changes in the marginaleffects package from
  version 0.29.0 onwards.

Bug fixes

• Fixed issue with find_formula() with mhurdle models.

insight 1.4.0

Breaking changes

• apply_table_theme() was removed, since it was an experimental feature that
  is no longer used in any package.

Changes

• display(), print_md() and print_html() get a .table method.

• get_predicted() now supports chisq.test(), and returns the expected
  frequencies.

• export_table() gains better support for the tinytable package. Use
  format = "tt" to export tables into the tinytable-format. This can also
  be used with grouped tables, i.e. by = "group".

• export_table() gains arguments row_groups and column_groups, to
  group rows and columns in the exported table. Column groups currently only
  work for format = "tt".

• If arguments title, subtitle and footer in export_table() are set to
  an empty string "", no titles/subtitles/footers are printed, even if present
  as attributes.

• Added a .lavaan method for is_converged().

• The formerly internal function to extract various information about mixed
  models is now exported as get_mixed_info().

Bug fixes

• Fixed issue with models of class selection with multiple response
  variables.

• Fixed issue in get_datagrid() for factors with = in their levels.

• Fixed issue in find_random() for multivariate response models of class brms
  with special response options.

• Fixed issue in several functions for certain betareg-models that contained
  a "mu" component instead of "mean".

• Fixed CRAN check issues on M1 Macs.

insight 1.3.1

Changes

• New function get_model() to extract the model object from an arbitrary
  object, if the model object is stored as attribute of the parent object.

• The range argument in get_datagrid() gets a new option, "pretty", to
  create a range of pretty values.

• get_predicted() now supports models of class glmtoolbox::glmee.

• get_predicted() supports predicting the class membership for models from
  package brms with mixture() family, using predict = "classificaton".

• get_predicted() supports predicting the outcome by class membership for
  models from package brms with mixture() family, using predict = "link".

• get_residuals() gets a method for objects from parameters::factor_analysis(),
  psych::fa(), psych::omega() and psych::principal().

• model_info() returns $is_mixture to identify finite mixture models.

• Better support for models of class sdmTMB.

• Improve efficiency of clean_parameters() for more complex brms models.

Bug fixes

• Fixed issue in get_df() for models from package afex.

• Fixed issue in clean_names() for brms models with mm() in formula.

• Fixed issue in get_data() for brms models with mmc() in formula.

• Fixed issue in get_statistic() for objects of class aov.

insight 1.3.0

Breaking Changes

• The default option "all" for the effects argument of find_parameters()
  and get_parameters() for models from package brms and rstanarm has a new
  behaviour and only returns fixed effects and random effects variance components,
  but no longer the group level estimates. Use effects = "full" to return
  all parameters. This change is mainly to be more flexible and gain more
  efficiency for models with many parameters and / or many posterior draws.

New functions

• is_bayesian_model() as a convenient shortcut to check whether a model is
  Bayesian or not.

Changes

• Revised wording for alerts from get_variance().

• The effects argument of find_parameters() and get_parameters() for
  models from package brms and rstanarm get two new options, "grouplevel"
  and "random_variances", to return only random effects variance components, or
  group level effects. This is more efficient especially for models with many
  samples and many parameters. Additionally, a variable argument can be passed
  to get_parameters(), which is in turn passed to as.data.frame(), to
  extract parameters more efficiently.

• The by argument in export_table() now also splits tables when format is
  not "html".

Bug fixes

• Fixed issue in find_formula() for models of class barts (package dbarts),
  when formula was abbreviated using y ~ ..

insight 1.2.0

Breaking Changes

• The handling of brms models in find_parameters(), find_formula() or
  clean_parameters() (and other functions) should now systematically take
  the many possible distributional parameters into account, identifying the
  different types of them, and assigning them to own values in the
  Component columns. insight should now be flexible enough to also cope
  with user-defined variables that have been modelled as distributional
  parameters.

• To be consistent with the naming pattern from package brms, all elements
  related to distributional parameters now returns exactly that "dpar" name.
  This means that, for instance, find_formula() no longer returns an element
  named $zero_inflated, but instead $zi. This only applies to models from
  brms! All other packages are not affected by this breaking change.

Changes

• find_random() and find_random_slopes() now also extract random effects
  names from auxiliary components.

• find_random() and find_random_slopes() now include random effects from the
  dispersion component for models from package glmmTMB.

• clean_parameters() for brms-models now assigns auxiliary parameters to their
  related Component and overwrites former assignments to "conditional".

• format_table() now includes more effect sizes when formatting column names.

• get_datagrid() now allows named vectors for arguments length and range,
  to match values with target variables defined in by.

• get_datagrid() gets a protect_integer argument, to allow a spread of
  values from minimum to maximum of length length, also for integer values.

• export_table() gets an argument column_names, to change the column names
  of the exported table.

• model_info() gains a response argument for classes that can be multivariate
  response models that return multiple lists of model information (currently,
  Stan models from rstanarm and brms). If not NULL, only the information
  for one of the response variables is returned.

• Creating a range of values in a get_datagrid() using by was now simplified
  and works like regular R syntax, e.g. by = "mpg = 20:50".

• get_predicted() for models of class brmsfit now supports Wiener models
  or similar so called "decision models", that simultaneously model, e.g.,
  reaction times and (discrete) choices.

• get_predicted() no longer throws warnings for models of class brmsfit
  when distributional are predicted.

• find_offset() gets an as_term argument, which returns the offset as term,
  including possible transformations.

• Token-option "quartiles2" was removed and option "quartiles" now produces
  the three quartile values (lower hinge, median, upper hinge). The former
  option of "quartiles" that included minimum and maximum was identical to the
  already existing "fivenum" option.

• New function find_auxiliary(), which is a small helper to extract all
  distributional parameters that were used in models from package brms.

• display(), print_md() and print_html() get methods for matrix- and
  array objects.

• Cleaning / revising package documentation.

Bug fixes

• null_model() now correctly calculates the null-model based on the data that
  was used to fit the model (model frame), which can lead to different results
  when the original data contained missing values.

• Fixed issue for get_predicted() with multivariate response models.

insight 1.1.0

Breaking Changes

• get_datagrid() no longer creates fractional parts when creating a range of
  values for numeric variables that are integers.

Changes

• get_datagrid() now includes a dummy column for model weights (values NA),
  to work with models that used weights.

• get_datagrid() gets a digits argument, to round numeric representative
  values.

• Argument ci_digits defaults to digits in format_table().

• format_table() gets a select argument, which can be used to select columns
  and column layout in a glue-like style.

• find_response() now also works for tidymodels workflows.

• get_transformation() and find_transformation() now also detect
  log-transformation with logarithmic base.

Bug fixes

• Fixed issue in find_formula(), find_response() and find_predictors() for
  multinomial gam models from package mgcv.

insight 1.0.2

Changes

• get_datagrid() gives a more informative error message when a variable
  specified in by was not found in the data.

• The by argument in get_datagrid() gets a new token-option, "[sample <number>]",
  to draw a random sample of values.

Bug fixes

• Option "terciles" and "terciles2" in get_datagrid() were swapped, i.e.
  "terciles" was doing what was documented for "terciles2" and vice versa.
  This has been fixed.

• include_random in get_datagrid() now works for nested random effects, i.e.
  for more than one group level factor in the random effects.

• Fixed issue in get_varcov() for models of class brmsfit that included
  monotonic effects.