parameters 0.20.1

General

• Added support for models of class flic and flac (logistf), mmrm (mmrm).

Changes

• model_parameters() now includes a Group column for stanreg or brmsfit
  models with random effects.

• The print() method for model_parameters() now uses the same pattern to
  print random effect variances for Bayesian models as for frequentist models.

Bug fix

• Fixed issue with the print() method for compare_parameters(), which
  duplicated random effects parameters rows in some edge cases.

• Fixed issue with the print() method for compare_parameters(), which
  didn't work properly when ci=NULL.

parameters 0.20.0

Breaking

• The deprecated argument df_method in model_parameters() is now defunct
  and throws an error when used.

• The deprecated functions ci_robust(), p_robust() and standard_error_robust
  have been removed. These were superseded by the vcov argument in ci(),
  p_value(), and standard_error(), respectively.

• The style argument in compare_parameters() was renamed into select.

New functions

• p_function(), to print and plot p-values and compatibility (confidence)
  intervals for statistical models, at different levels. This allows to see
  which estimates are most compatible with the model at various compatibility
  levels.

• p_calibrate(), to compute calibrated p-values.

Changes

• model_parameters() and compare_parameters() now use the unicode character
  for the multiplication-sign as interaction mark (i.e. \u00d7). Use
  options(parameters_interaction = <value>) or the argument interaction_mark
  to use a different character as interaction mark.

• The select argument in compare_parameters(), which is used to control the
  table column elements, now supports an experimental glue-like syntax.
  See this vignette Printing Model Parameters. Furthermore, the select
  argument can also be used in the print() method for model_parameters().

• print_html() gets a font_size and line_padding argument to tweak the
  appearance of HTML tables. Furthermore, arguments select and column_labels
  are new, to customize the column layout of tables. See examples in ?display.

• Consolidation of vignettes on standardization of model parameters.

• Minor speed improvements.

Bug fix

• model_parameters().BFBayesFactor no longer drops the BF column if the
  Bayes factor is NA.

• The print() and display() methods for model_parameters() from Bayesian
  models now pass the ... to insight::format_table(), allowing extra
  arguments to be recognized.

• Fixed footer message regarding the approximation method for CU and p-values
  for mixed models.

• Fixed issues in the print() method for compare_parameters() with mixed
  models, when some models contained within-between components (see
  wb_component) and others did not.

parameters 0.19.0

Breaking

• Arguments that calculate effectsize in model_parameters() for htest,
  Anova objects and objects of class BFBayesFactor were revised. Instead of
  single arguments for the different effectsizes, there is now one argument,
  effectsize_type. The reason behind this change is that meanwhile many
  new type of effectsizes have been added to the effectsize package, and
  the generic argument allows to make use of those effect sizes.

• The attribute name in PCA / EFA has been changed from data_set to dataset.

• The minimum needed R version has been bumped to 3.6.

• Removed deprecated argument parameters from model_parameters().

• standard_error_robust(), ci_robust() and p_value_robust() are now
  deprecated and superseded by the vcov and vcov_args arguments in the
  related methods standard_error(), ci() and p_value(), respectively.

• Following functions were moved from package parameters to performance:
  check_sphericity_bartlett(), check_kmo(), check_factorstructure() and
  check_clusterstructure().

Changes to functions

• Added sparse option to principal_components() for sparse PCA.

• The pretty_names argument from the print() method can now also be
  "labels", which will then use variable and value labels (if data is
  labelled) as pretty names. If no labels were found, default pretty names
  are used.

• bootstrap_model() for models of class glmmTMB and merMod gains a
  cluster argument to specify optional clusters when the parallel
  option is set to "snow".

• P-value adjustment (argument p_adjust in model_parameters()) is now
  performed after potential parameters were removed (using keep or drop),
  so adjusted p-values is only applied to the parameters of interest.

• Robust standard errors are now supported for fixest models with the vcov
  argument.

• print() for model_parameters() gains a footer argument, which can be
  used to suppress the footer in the output. Further more, if footer = ""
  or footer = FALSE in print_md(), no footer is printed.

• simulate_model() and simulate_parameters() now pass ... to
  insight::get_varcov(), to allow simulated draws to be based on
  heteroscedasticity consistent variance covariance matrices.

• The print() method for compare_parameters() was improved for models with
  multiple components (e.g., mixed models with fixed and random effects, or
  models with count- and zero-inflation parts). For these models,
  compare_parameters(effects = "all", component = "all") prints more nicely.

Bug fixes

• Fix erroneous warning for p-value adjustments when the differences between
  original and adjusted p-values were very small.

parameters 0.18.2

New functions

• New function dominance_analysis(), to compute dominance analysis
  statistics and designations.

Changes to functions

• Argument ci_random in model_parameters() defaults to NULL. It uses a
  heuristic to determine if random effects confidence intervals are likely to
  take a long time to compute, and automatically includes or excludes those
  confidence intervals. Set ci_random to TRUE or FALSE to explicitly
  calculate or omit confidence intervals for random effects.

Bug fixes

• Fix issues in pool_parameters() for certain models with special components
  (like MASS::polr()), that failed when argument component was set to
  "conditional" (the default).

• Fix issues in model_parameters() for multiple imputation models from
  package Hmisc.

parameters 0.8.3

Release for JOSS

parameters 0.8.2

on CRAN

parameters 0.8.1

Update DESCRIPTION

0.2.0

• CRAN Release (0.2.0)