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.

insight 1.0.1

General

• Support for models of class oohbchoice (package DCchoice).

• format_table() gets a stars_only argument, to format p-value columns to
  contain only significance stars.

• get_predicted() for brms-models with categorical family now includes the
  data of the data grid in the returned predictions, for better orientation.

Bug fixes

• Fixed issues due to latest mice updates.

• Fixed typo in get_parameters.glmmadmb(), which was erroneously renamed into
  get_parameters.glmmTMBadmb().

• Fixed issues in find_predictors() and has_intercept() for brms models
  with 0 + Intercept formula notation.

• Fixed issues in get_statistic() for models of class fixest from
  negative-binomial families.

• Fixed issue with as.numeric() method for get_sigma().

• get_datagrid() now only returns valid levels when include_random = TRUE
  and group-level factor in random effects is numeric.

insight 1.0.0

Breaking changes

• All deprecated arguments have been removed.

• The table_width argument in export_table() now defaults to "auto".

General

• get_transformation() can now deal with any power-transformation, and also
  returns results for divisions (scaled response) and Box-Cox transformations.

• find_transformation() and get_transformation() now also detects use of
  divisions, like x/3 or Box-Cox transformations (like (x^lambda - 1) / lambda).

• find_transformation() and get_transformation() get a include_all argument,
  to check all model terms for transformations.

• get_dispersion() is now an exported function.

• Updated get_varcov() (and related documentation) to support new covariance
  matrix estimation methods from the sandwich package.

• New function validate_argument() as a replacement for match.arg() with
  more informative error message.

• The function to calculate the corrections for likelihood-values when the
  response-variable is transformed is now exported as get_likelihood_adjustment().

• export_table() can now split tables into more than three tables when
  table_width is used (formerly, the maximum number of split tables was three).

• Changed (improved) formatting for parameter tables in export_table(), when
  format = "html". Rows are indented, and group headers are emphasized in
  italic.

• formula_ok() now also checks for syntactically invalid variable names.
  Furthermore, argument checks now allows to specify for which possibly
  problematic formula notation should be checked.

• format_value() gains a decimal_point argument, to change the decimal point
  in output conversion.

• format_bf() with stars = TRUE uses the ° symbol for inferiority
  (evidence against the comparison).

• Added support for coxph.panel models.

• Added support for models of class asym (package panelr).

• Overhaul of documentation for the package-functions.

Bug fix

• clean_parameters() now uses the correct labels for the random effects
  variances ("SD/Cor" has changed to "Var/Cov").

• When get_data() could not properly evaluate the subset of a data set, it
  now returns an informative warning and no longer errors.

• Fixed inaccuracy in get_sigma() for models of class brmsfit.

• Fixed issues in get_variance() for models of class brmsfit when the
  sigma-parameter was directly modeled.

• Fixed issue in compact_character() and compact_list() for date-variables.

• Fixed edge case in find_transformation() for simple log-transformation of
  the response variable.

• Fixed issue for model_info.averaging().

insight 0.20.5

General

• get_datagrid() can now be used to extract the "grid" information from
  {emmeans} and {marginaleffects} outputs.

• Arguments na.rm and na_rm are deprecated throughout the package's functions.
  Instead, use remove_na.

Bug fixes

• Fixed rendering issue of the example in ?insight::display.

• Fixed issues due to recent changes in the glmmTMB package.

insight 0.20.4

New supported models

• Support for models of classes glm_weighit, multinom_weightit and
  ordinal_weightit (package WeightIt).

Changes

• null_model() and formula_ok() now warn when indexed data frames, such as
  df[, 5], are used as response variable in the formula, as this can lead to
  unexpected results.

• Minor improvements to link_function() and link_inverse().

Bug fixes

• Fixed regression from latest fix related to get_variance() for brms models.

• Fixed issue in link_function() and link_inverse() for models of class
  cglm with "identity" link, which was not correctly recognized due to a
  typo.

insight 0.20.3

Changes

• get_df() now supports more model classes.

• get_variance() gives an informative error if no mixed model is provided.

Bug fixes

• Fixed issue in find_formula(), find_predictors() and find_variables()
  for models from package brms with custom formulas.

• Fixed issues in find_response() for brms models with mi() function in
  the response variable.

• Fixed issue in get_variance() that could lead to recursive calls for
  brms models, resulting in "infinite" resampling of the model.

• Fixed issue in check_if_installed() that erroneously tried to guess the
  minimum required package version based on the SUGGEST field of the insight
  package, instead of the package that was calling the function.

• Fixed issue in get_modelmatrix() for models from package brms with
  special functions in the formula (like mo()).

• Fixed issue in ellipses_info() when this function was called from do.call().

• Fixed issue with formatting unicode-symbols, where a wrong unicode-character
  was used for "Omega". Furthermore, Omega2 and Eta2 are now correctly converted.

insight 0.20.2

New supported models

• Support for models of class glmgee (package glmtoolbox).

• Support for models of class svy2lme (package svylme).

General

• Massive overhaul of get_variance(). The function should be now more
  accurate for different distributional families, in particular for
  mixed regression models with Beta family.

• Improved accuracy of singularity-checks in get_variance().

• get_variance() gets a few new arguments:

  • null_model, to provide a null-model to be used for the calculation of
    random effect variances. If NULL, the null-model is computed internally.
    This argument is optional, but may be useful to save time, or when the
    null-model cannot be calculated internally.

  • approximation, indicating the approximation method for the
    distribution-specific (observation level, or residual) variance.

  • model_component, for models that can have a zero-inflation component,
    specify for which component variances should be returned. By default, both
    the conditional and the zero-inflation component are taken into account.

• format_alert() and format_warning() get an immediate argument, to output
  warnings immediately.

• find_terms() and find_transformation() now better cope with inverse
  transformations of the response value, such as 1/y.

• get_transformation() now returns more transformations for power-transformed
  response variables.

• model_info() for MixMod objects from package GLMMadaptive now recognize
  zero-inflation and hurdle models for custom families.

Bug fixes

• null_model() now correctly handles zero-inflated models from package
  glmmTMB.

• Fixed issue in null_model() for models from package GLMMadaptive.

• Fixed issues in link_inverse() and link_function() for models of class
  gamlss from LOGNO() family.