insight 0.18.6

Bug fixes

• Better dectection of unicode-support, to avoid failures when building
  vignettes.

• get_predicted() now correctly handles variables of class numeric matrix
  created by scale(), which fixes a bug in performance::check_model()
  (easystats/performance#432).

• Fixed issue with iterations argument in get_predicted() with brms
  models.

• Support the logitr package: get_data(), find_variables() and more.

insight 0.18.5

Breaking

• get_df(type = "satterthwaite") for lmerMod objects now return degrees of
  freedom per parameter, and no longer per observation. Use df_per_obs TRUE
  to return degrees of freedom per observation.

New functions

• safe_deparse_symbol() to only deparses a substituted expressions when
  possible,which increases performance in case many calls to
  deparse(substitute()).

Changes to functions

• format_table() gets a use_symbols argument. If TRUE, column names that
  refer to particular effectsizes (like Phi, Omega or Epsilon) include the related unicode-character instead of the written name. This only works on Windows for
  R >= 4.2, and on OS X or Linux for R >= 4.0.

• The stars argument in format_table() can now also be a character vector,
  naming the columns that should include stars for significant values. This is
  especially useful for Bayesian models, where we might have multiple columns
  with significant values, e.g. "BF" for the Bayes factor or "pd" for the
  probability of direction.

• get_df() gets more type options to return different type of degrees of
  freedom (namely, "wald" and "normal", and for mixed models, "ml1",
  "betwithin", "satterthwaite" and "kenward-roger").

• standardize_names() now recognized more classes from package marginaleffects.

• Minor improvements to find_parameters() for models with nonlinear formula.

• Minor speed improvements.

Bug fixes

• Fixed issue in get_data() for models of class plm, which accidentally
  converted factors into character vectors.

• Fixed issue with column alignment in export_table() when the data frame
  to print contained unicode-characters longer than 1 byte.

• Correctly extract predictors for fixest::i(f1, i.f2) interactions (#649 by
  @grantmcdermott).

insight 0.18.4

Changes to functions

• model_info() now includes information for htest objects from
  shapiro.test() and bartlett.test() (will return $is_variancetest = TRUE).

Bug fixes

• Fixed issue in get_data() which did not correctly backtransform to original
  data when terms had log-transformations such as log(1 + x) or log(x + 1).

insight 0.18.3

New functions

• format_alert(), format_warning() and format_error(), as convenient
  wrappers around message(), warning() or stop() in combination with
  format_message(). You can use these functions to format messages, warnings
  or errors.

Changes to functions

• get_predicted() for models of class clm now includes confidence intervals
  of predictions.

• format_message() gets some additional formatting features. See 'Details'
  in ?format_message for more information and some current limitations.

• format_message() gets an indent argument, to specify indention string
  for subsequent lines.

• format_table() now merges IC and IC weights columns into one column (e.g.,
  former columns "AIC" and "AIC_wt" will now be printed as one column, named
  "AIC (weights)"). Furthermore, an ic_digits argument was added to control
  the number of significant digits for the IC values.

• print_color() and color_text() now support bright variants of colors and
  background colors.

• get_datagrid() gets more options for at and range, to provide more
  control how to generate the reference grid.

• get_data() for models of class geeglm and fixestnow more reliably
  retrieves the model data.

New supported models

• Support for models of class mblogit and mclogit.

Bug fixes

• Fixed issues with wrong attribute adjusted_for in insight::get_datagrid().

• Fixed issue (resp. implemented workaround) in get_data.iv_robust(), which
  failed due to a bug in the estimatr package.

• Fixed issue where get_predicted() failed when data contains factors with
  only one or incomplete levels.

• Fixed issue in get_predicted() for models of class mlm.

• Fixed issue where get_predicted() failed to compute confidence intervals
  of predictions when model contained matrix-alike response columns, e.g. a
  response variable created with cbind().

insight 0.18.2

New functions

• format_percent() as short-cut for format_value(as_percent = TRUE).

• is_converged(), to check whether a mixed model has converged or not.

Changes to functions

• format_table() gains an exact argument, to either report exact or rounded
  Bayes factors.

• get_predicted() gets a method for models of class gamlss (and thereby,
  get_loglikelihood() now also works for those model classes).

• get_predicted() now better handles models of class polr, multinom and
  rlm.

Bug fixes

• Fixed test failures.

• Minor fixes to address changes in other packages.

insight: A Unified Interface to Access Information from Model Objects in R

When fitting any statistical model, there are many useful pieces of information that are simultaneously calculated and stored beyond coefficient estimates and general model fit statistics. Although there exist some generic functions to obtain model information and data, many package-specific modeling functions do not provide such methods to allow users to access such valuable information.

insight is an R-package that fills this important gap by providing a suite of functions to support almost any model (see a list of the many models supported below in the List of Supported Packages and Models section). The goal of insight, then, is to provide tools to provide easy, intuitive, and consistent access to information contained in model objects. These tools aid applied research in virtually any field who fit, diagnose, and present statistical models by streamlining access to every aspect of many model objects via consistent syntax and output.

insight: A Unified Interface to Access Information from Model Objects in R

When fitting any statistical model, there are many useful pieces of information that are simultaneously calculated and stored beyond coefficient estimates and general model fit statistics. Although there exist some generic functions to obtain model information and data, many package-specific modeling functions do not provide such methods to allow users to access such valuable information. 

insight is an R-package that fills this important gap by providing a suite of functions to support almost any model (see a list of the many models supported below in the List of Supported Packages and Models section). The goal of insight, then, is to provide tools to provide easy, intuitive, and consistent access to information contained in model objects. These tools aid applied research in virtually any field who fit, diagnose, and present statistical models by streamlining access to every aspect of many model objects via consistent syntax and output.