parameters 0.29.2

Changes

• simulate_model(), simulate_parameters() and equivalence_test() now work
  for lavaan objects.

• Added format() method for objects returned by factor_analysis() and
  principal_components().

Bug fixes

• Fixed issues with extracting wrong standard errors for model with frailty
  terms in survival::coxph().

• Fixed issue where including a character variable in a model caused all other
  variable labels to be silently dropped from model_parameters() output
  (#1142).

• Fixed issue where on-the-fly factor conversions in the model formula (e.g.,
  factor(cyl)) produced NA in interaction labels when variable labels were
  set (#1135).

• Fixed issue where include_reference = TRUE had no effect for
  pscl::zeroinfl() and pscl::hurdle() models (#1130).

• Fixed issue with calculation of standard errors in model_parameters() when
  vcov was a function that errored when unsupported arguments were passed.

• Fixed issue in print_html() for model_parameters() with lavaan objects.

parameters 0.29.1

Changes

• bootstrap_model() for non-mixed models also gains a cluster argument for use
  if parallel = "snow".

Bug fixes

• The vcov argument in model_parameters() was ignored when vcov was of
  class "dpoMatrix" and did not return TRUE to is.matrix().

• Fixed issue with vcov argument in model_parameters() for models of class
  glmmTMB.

• Fixed issue with printing study names in brms-meta-analysis models.

• Fixed failing example in CRAN checks.

parameters 0.29.0

Changes

• standardize_parameters() (and by extension model_parameters()) with any of
  the post-hoc standardization methods no longer standardizes the
  "(Intercept)" parameter - instead setting it to NA.

• standardize_parameters() with any of the post-hoc standardization methods
  sets all inferential statistics (z, p, etc...) for the "(Intercept)" and any
  other NA parameters to NA.

• model_parameters() now supports objects from the lavaan.mi package.

• Improved performance of model_parameters() for large mgcv::gam() models
  that include random effects when using the new re_test argument (e.g.,
  setting re_test = FALSE to skip expensive random-effect tests). Default
  behavior (with re_test = TRUE) is unchanged.

• model_parameters() for proportions-htests objects no longer hard-codes the
  estimate for the proportion in the underlying data frame. This is now done
  in the format() method.

• model_parameters() now supports htests objects from package BSDA.

• Output for other random effects covariance structures than "unstructured" for
  models from package glmmTMB has been revised, to provide a more useful output,
  which is also in line with the relevant information returned by VarCorr().

Bug fixes

• Fixed issue where wrong (non-robust) standard errors were calculated for
  coxph and svycoxph objects.

• Fixed issues with Tukey-p-value adjustment for emmeans objects.

• Fixed unintended removal of columns in model_parameters() for objects from
  package marginaleffects. This happened, when a variable in a model was named
  Type.

• Fixed issue in model_parameters() for fisher.test() with tables larger
  than 2x2.

parameters 0.28.3

• fixed bug in standardize_info(<fixest>) that was preventing
  standardise_parameters() from working for fixest models.

• equivalence_test() gets methods for objects from the modelbased package.

• Improved support for objects from package survey.

• Added support for package lcmm.

• Added ci_method options "kenward-roger" and "satterthwaite" for models
  from package glmmTMB. Consequently, se_kenward(), se_satterthwaite(),
  ci_kenward(), ci_satterthwaite(), p_value_kenward() and
  p_value_satterthwaite() can now be used with glmmTMB models.

parameters 0.28.2

Bug fixes

• Updates tests to resolve issues with the latest version of the fixest package.

parameters 0.28.1

Changes

• Methods for glmmTMB objects (ci(), model_parameters(), standard_error())
  now support the vcov argument to compute robust standard errors.

• model_parameters() for marginaleffects objects is now more robust in
  detecting Bayesian models.

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

Bug fixes

• Fixed issue with equivalence_test() for models of class glmmTMB with
  beta_family().

• exponentiate = TRUE in model_parameters() did not exponentiate location
  and scale parameters for models from package ordinal.

parameters 0.28.0

Breaking Changes

• The experimental print_table() function was removed. The aim of this function
  was to test the implementation of the tinytable backend for printing. Now,
  tinytable is fully supported by insight::export_table() and thereby also
  by the various print() resp. display() methods for model parameters.

Changes

• All print_html() methods get an engine argument, to either use the gt
  package or the tinytable package for printing HTML tables. Since tinytable
  not only produces HTML tables, but rather different formats depending on the
  environment, print_html() may also generate a markdown table. Thus, the
  generic display() method can be used, too, which has a format argument that
  also supports "tt" for tinytable.

• Improved support for coxme models in model_parameters(). Random effects
  and group level estimates are now returned as well.

Bug fixes

• Fixed issue with models of class selection with multiple outcomes.

parameters 0.27.0

Breaking Changes

• The standardize argument in factor_analysis() now defaults to FALSE.

• The rotation argument in factor_analysis() now defaults to "oblimin",
  because the former default of "none" rarely makes sense in the context of
  factor analysis. If you want to use no rotation, please set rotation = "none".

• The cor argument in n_factors() was renamed into correlation_matrix. In
  factor_analysis(), the cor argument was completely removed to avoid naming
  collision with the cor argument of psych::fa(), which now users can pass
  the cor argument to psych::fa() when using factor_analysis().

Changes

• factor_analysis() gets a .matrix method, including arguments n_obs and
  n_matrix, to compute factor analysis for a correlation matrix or covariance
  matrix.

• New function factor_scores() to extract factor scores from EFA (psych::fa()
  or factor_analysis()).

• Added and/or improved print-methods for all functions around PCA, FA and Omega.

• Improved efficiency in model_parameters() for models from packages brms
  and rstanarm.

• p_adjust for model_parameters() gets a new options, "sup-t", to calculate
  simultaneous confidence intervals.

Bug fixes

• bootstrap_model() did not work for intercept-only models. This has been fixed.

• Fixed issue with printing labels as pretty names for models from package
  pscl, i.e. print(model_parameters(model), pretty_names = "labels") now
  works as expected.

parameters 0.26.0

Changes

• The effects argument in model_parameters() for classes merMod, glmmTMB,
  brmsfit and stanreg gets an additional "grouplevel" option, to return
  the group-level estimates for random effects.

• model_parameters() for Anova-objects gains a p_adjust argument, to apply
  p-adjustment where possible. Furthermore, for models from package afex, where
  p-adjustment was applied during model-fitting, the correct p-values are now
  returned (before, unadjusted p-values were returned in some cases).

• Revised code-base to address changes in latest insight update. Dealing with
  larger models (many parameters, many posterior samples) from packages brms
  and rstanarm is more efficient now. Furthermore, the options for the
  effects argument have a new behaviour. "all" 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.

• model_parameters() for Anova objects gains an include_intercept argument,
  to include intercepts in the Anova table, where possible.

parameters 0.25.0

Changes

• model_parameters() for objects from the marginaleffects packages now calls
  bayestestR::describe_posterior() to process Bayesian models. This offers
  more flexibility in summarizing the posterior draws from marginaleffects.

• model_parameters() now shows a more informative coefficient name for binomial
  models with probit-link.

• Argument wb_component now defaults to FALSE.

• Improved support and printing for tests from package WRS2.

Bug fixes

• Fixed printing issue with model_parameters() for htest objects when
  printing into markdown or HTML format.

• Fixed printing issue with model_parameters() for mixed models when
  include_reference = TRUE.