Support for objects of class ggcomparisons from ggeffects::hypothesis_test().
brms::gr() is now supported, meaning that functions like get_data() or find_predictors() now also work for models with group-specific random effects.
Fix CRAN check issues due to the last fixest update.
get_varcov() for models of class pgmm (package plm) now also supported robust variance-covariance matrices (i.e. argument vcov).Fixed issue in find_predictors() for survival models with strata(), containing more that one variable.
Fixed issue in model_info(), where in some cases logistic regression models were erroneously considered as "bernoulli" models.
Fixed issue in find_formula() for models of class gamlss when the random() function was used with namespace in the formula (i.e. ... + gamlss::random()).
model_info() now detects models with zero-inflation part from package glmmTMB when models have truncated-families but no ziformula.
get_predicted_ci().model_info() now recognized ordered beta families.
find_formula and get_response for nestedLogit models gain a dichotomies argument, to return values for the dichotomies used to fit the model.
find_transformation() better detects power-transformation of the response variable.
Corrected return value from find_statistic for nnet::multinom() models.
clean_parameters() did not return the "clean_parameters" class attributes for some object. This caused issued in upstream packages.
Fixed issue in model_info(), which did not correctly detect “Bernoulli” property for some models classes (like glmmTMB or glmerMod).
check_if_installed() for old R releases.get_predicted() now accepts predict = "link" for gaussian models with log-link (i.e. glm(..., family = gaussian("log"))), to return predictions on the link scale.
check_if_installed() now automatically checks the package DESCRIPTION file to determine the correct minimum version required.
Fixed issue with invalid multibyte strings in trim_ws().
Fixed issue in find_statistic() for models from package fixest.
standardize_column_order() has changed the position when re-ordering Bayes factors, ROPEs and ESS / Rhat (mainly relevant for Bayesian models).standardize_names() and standardize_column_order() now also recognize the "response.level" column name.
get_data() for lavaan models is now more stable at retrieving model data when this is not available in the environment.
find_terms() gets an as_term_labels argument, to extract model terms from the formula’s "term.labels" attribute. This is closer to the behaviour of stats::terms(), but may be insufficient, e.g. for mixed models.
get_random() now returns the same observations as get_data() and correctly removes missing values from the data before returning it.
find_parameters() for marginal effects ignores the "s.value" column (which was added in a recent update).
Fixed issue in get_response() for brms models with trunc() function in the response variable.
The minimum needed R version has been bumped to 3.6.
download_model() no longer errors when a model object could not be downloaded, but instead returns NULL. This prevents test failures, and allows to skip tests when the return value of download_model() is NULL.
mclogit models (package mclogit) and mipo objects (package mice) for models with ordinal or categorical response.phylolm and phyloglm (package phylolm), nestedLogit (package nestedLogit).Fixed issue in get_variance() for glmmTMB models with rank deficient coefficients.
Fixed issues in get_weights() for glm models without weights and na.action not set to default in the model call.
clean_names() now also removes the relevel() pattern.
Fixed issue in model_info() for models of class gamlss.
Fixed problems preventing get_data() from locating data defined in non-global environments.
Fixed issue in get_predicted() for variables of class numeric matrix created by scale(), which were correctly handled only when get_data() failed to find the data in the appropriate environment.
Fixed issue in model_info() for gee models from binomial families.
hglm (package hglm).Minor improvements to get_data() for t.test().
format_value() gets a lead_zero argument, to keep or drop the leading zero of a formatted value, as well as arguments style_positive and style_negative to style positive or negative numbers.
format_table() now also formats columns named SGPV (second generation p-values) as p-values.
Functions for models of class clm (like find_formula(), find_variables(), get_data() etc.) now also include variables that were defined as scale or nominal component.
Fixed issue in get_data() for results from kruskal.test().
Fixed issue in find_weights() for models of class lme and gls.
Fixed issue in get_datagrid() for models with multiple weight variables.
mmrm (package mmrm), flac and flic (logistf)get_data() was revised and now always tries to recover the data that was used to fit a model from the environment. If this fails, it falls back to recovering data from the model frame (the former default behaviour). Furthermore, the source argument can be used to explicitly force the old behaviour: source = "mf" will try to recover data from the model frame first, then possibly falling back to look in the environment.n_grouplevels(), to return random effect groups and number of group levels for mixed models.get_datagrid() preserves all factor levels for factors that are hold constant at their reference level. This is required to work together with get_modelmatrix() when calculating standard errors for get_predicted().Fixed but in get_modelmatrix() handling of incomplete factors which sometimes had downstream implications for numerical results in the uncertainty estimates produced by get_predicted().
Fixed minor issues for HTML tables in export_table() when model parameters were grouped.
Fixed issue with incorrect back-transforming in get_data() for models with log-transformed variables.
Fixes issue in compact_list().
has_single_value() now returns FALSE when the object only has NA and na.rm = TRUE.
Fixed issue in get_parameters() for gam-models without smooth terms, or with only smooth terms and removed intercept.
Minor revisions to get_predicted.glmmTMB() due to changes in behaviour of predict.glmmTMB() for truncated-family models since glmmTMB 1.1.5.
New function has_single_value() that is equivalent to length(unique()) == 1 (or n_unique() == 1) but faster.
ellipses_info() now includes an attribute $is_binomial, which is TRUE for each model from binomial family.Fixed behaviour of the at argument in get_datagrid().
Fixed issue for accessing model data in get_datagrid() for some edge cases.
get_data(), find_variables() and more.Better detection 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.
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.safe_deparse_symbol() to only deparses a substituted expressions when possible,which increases performance in case many calls to deparse(substitute()).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.
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).
model_info() now includes information for htest objects from shapiro.test() and bartlett.test() (will return $is_variancetest = TRUE).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).
Fixed CRAN check issues.
format_alert(), format_warning() and format_error(), as convenient wrappers around message(), warning() or stop() in combination with format_message(). You can use these funcionts to format messages, warnings or errors.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.
mblogit and mclogit.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().
format_percent() as short-cut for format_value(as_percent = TRUE).
is_converged(), to check whether a mixed model has converged or not.
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.
Fixed test failures.
Minor fixes to address changes in other packages.
The ci argument in get_predicted() now defaults to NULL. One reason was to make the function faster if confidence intervals are not required, which was the case for many downstream usages of that function. Please set ci explicitly to compute confidence intervals for predictions.
get_data() no longer returns logical types for numeric variables that have been converted to logicals on-the-fly within formulas (like y ~ as.logical(x)). Instead, for each numeric variable that was coerced to logical within a formula gets a logical attribute (set to TRUE), and the returned data frame gets a logicals attribute including all names of affected variables.
parameters_table(), the alias for format_table(), was removed.
find_transformation() and get_transformation() now also work for models where the response was transformed using log2() or log10().get_sigma() for models from package VGAM returned wrong sigma-parameter.
find_predictors() for models from package fixest that contained interaction terms in the endogenous formula part did not correctly return all instruments.
Fixed formatting of HTML table footers in export_table().
Several fixes to get_predicted() for models from mgcv::gam().
The component argument in find_parameters() for stanmvreg models did not accept the "location" value.
null_model() did not consider offset-terms if these were specified inside formulas.
Argument allow.new.levels was not passed to predict() for get_predicted.glmmTMB().
clean_names() now works correctly when several variables are specified in s() (#573, @etiennebacher).
deltaMethod (car), marginaleffects, marginaleffects.summary (marginaleffects)get_predicted() now supports models of class iv_robust and ivreg.
For get_predicted(), when both type and predict are given, type will overwrite predict. Note that this will print a message, because predict is the preferred argument.
get_varcov() gains vcov and vcov_args arguments, to specify the variance-covariance matrix used to compute uncertainty estimates (e.g., for robust standard errors).
get_loglikehood() improved handling of models from package estimator.
Fixed bug in get_data() for model objects whose data needs to be recovered from the environment, and where the data name was a reserved word (e.g., named like an R function).
The matrix returned by get_varcov() for models of class bife now returns row and column names.
find_offset() did not find offset-terms for merMod objects when the offset was specified as offset argument in the function call.
vcov_estimation and vcov_type in get_predicted(), get_predicted_se() and get_predicted_ci() are replaced by vcov and vcov_args, to have a more simplified and common interface to control robust covariance matrix estimation.get_data() and model_info().To check for names: object_has_names() and object_has_rownames()
To work with lists: is_empty_object() and compact_list()
To work with strings: compact_character()
Further utility functions are safe_deparse(), trim_ws() and n_unique().
export_table() now better checks for invalid values of caption and footer for tables in HTML format, and silently removes, e.g., ansi-colour codes that only work for text-format.
get_data.coxph() returns the original data frame instead of data with type coercion.
get_loglikelihood() gets a check_response argument, to check if a model has a transformed response variable (like log() or sqrt() transformation), and if so, returns a corrected log-likelihood.
get_modelmatrix() now supports BayesFactor models.
get_loglikelihood() and get_df() now support more model classes.
get_predicted() was improved for multinomial models from brms.
get_variance() was improved to cover more edge cases of (more complex) random effect structures.
get_data() now includes variables in the returned data frame that were used in the subset argument of regression functions (like lm()).
In some edge cases, where get_data() is unable to retrieve the data that was used to fit the model, now a more informative error is printed.
ellipses_info() now also accepts a list of model objects, is more stable and returns more information about the provided models (like if all fixed or random effects are the same across models, if all models are mixed models or null-models, etc.)
check_if_installed() now works interactively and lets the user prompt whether to automatically update or install packages.
Fixed incorrect column name conversion in standardize_names() for certain columns returned by broom::glance().
Fixed issue with correctly detecting Tweedie-models in model_info().
Fixed issue with get_datagrid() for brms models with monotonic factors.
Fixed issue in find_formula() when argument correlation was defined outside of lme() and gls() (@etiennebacher, #525).
Fixed issue with get_data() when back-transforming data from predictors that used cos(), sin() or tan() transformations.
get_datagrid(), to generate a reference grid, usually used when computing adjusted predictions or marginal means from regression models.get_predicted()get_predicted() was revised. Beside the four core options for the predict argument, it is now also possible to use any value that is valid for the model’s predict() method’s type argument.
get_predicted() now supports more models (e.g., from packages like GLMMadaptive or survival).
get_predicted() is now more robust when calculating standard errors of predictions.
get_statistic() and find_statistic() now support htest objects.get_data().get_data() for coxph models now returns the original factor levels for variables transformed with strata() inside formulas.Data management functions (like reshape_longer(), or data_match()) have been moved to the datawizard package.
get_data() no longer returns factor types for numeric variables that have been converted to factors on-the-fly within formulas (like y ~ as.factor(x)). Instead, for each numeric variable that was coerced to factor within a formula gets a factor attribute (set to TRUE), and the returned data frame gets a factors attribute including all names of affected variables.
bfsl (bfsl)standardize_column_order() function can be used to standardize the column order in output dataframes.Improved speed performance for some functions.
Improved handling of table captions and footers in export_table(). See also the new vignette on exporting data frames into human readable tables here: https://easystats.github.io/insight/articles/export.html
Revised width argument in export_table(), which now allows to set different column widths across table columns. See examples in ?export_table.
export_table() gets a table_width argument to split wide tables into two parts.
get_varcov() for MixMod (package GLMMadaptive) was revised, and now allows to return a robust variance-covariance matrix.
Added more get_df() methods.
Fixed issues with manual sigma computation to handle dispersion models in get_sigma().
Fixed issue in find_formula() for BayesFactor::lmBF() with multiple random effects.
Fixed issue in get_parameters.BFBayesFactor() with wrong sign of difference estimate for t-tests.
Argument width in format_value() was ignored when formatting integer values and protect_integers was set to TRUE.
find_transformation() and get_transformation() to find or get any function that was used to transform the response variable in a regression model.Improved support for models of class sampleSelection.
Improved documentation.
get_modelmatrix() now supports: rms::lrm
get_predicted() supports: MASS::polr, MASS::rlm, rms::lrm, fixest, bife::bife, ordinal::clm.
get_predicted() standard errors are often much faster to compute.
get_predicted() supports models with “grouped” or “level” outcomes (e.g., multinomial logit).
get_predicted() handles factors better.
Improved documentation
check_if_installed() gains a quietly argument, if neither stopping nor a warning message for non-installed packages is requested.
get_predicted()’s predict argument now accepts these values: “link”, “expectation”, “prediction”, “classification”, or NULL.
get_predicted() accepts predict=NULL, which allows users to push a type argument through the ... ellipsis, forward to the predict() method of the modelling package.
Fixed issue with parameter names from emmeans objects in get_parameters().
Fixed issues with unknown arguments in get_predicted().
systemfit (systemfit)get_predicted() gains a new option, predict = "response" for binomial models.
Improved stability of get_variance() when computing random-slope-intercept correlation with categorical random slopes.
Improved get_priors() for brms models.
Fixed issue in get_data() for brms models with auxiliary parameters.
Fixed issue in find_formula() for brms models with auxiliary parameters.
Fixed issue where get_data() for htest objects did not always preserve factors.
Fixed issue in format_table() for ci-levels with longer fractional part.
check_if_installed() gains a minimum_version argument, to check if an installed package is not older than the specified version number.
The package argument in check_if_installed() is now vectorized, so you can check for multiple packages in one function call.
Value formatting functions (like format_value() or format_ci()) can now round to significant digits using digits = "signif".
Fixed issue in model_info() with stan_polr() models.
Fixed issue in find_parameters() for brms when model contained parameters for the priors on sigma.
Fixed issue in n_obs() for stats4::mle() models.
Fixed failing tests due to latest fixest update.
Fixed issues due to latest epiR update.
data_to_long(), data_match(), data_relocate(), data_restoretype(), force_numeric().pgmm (plm)Stability improvements to get_predicted().
Fixed issues when accessing information from an afex_aov model with an empty aov slot (in anticipation for {afex} v.1.0.0).
Fixed issue in model_info() for stanreg object with non-standard model-family specification.
get_sigma() and get_auxiliary(), as well as get_parameters(component = "all")) for brmsfit models.get_modelmatrix() as a robust alternative to model.matrix() for different model classes.
format_message() to format warnings and messages by adjusting the maximum line_length, possibly to the width of the console window.
format_string() to shorten a string to a maximum length.
check_if_installed() to see if the needed package is installed.
mvord (mvord), SemiParBIV (GJRM), selection (sampleSelection)find_formula() now warns when data name is present in formula, since this can result in unexpected behaviour in other package functions.
model_info() returns is_bernoulli = TRUE for Bernoulli models.
Add get_statistic() for lavaan models.
get_df() supports more models/objects.
get_sigma() supports more models/objects.
get_sigma() and get_deviance() for lrm models (package rms) now only return one value, sigma or deviance for the model with intercept and predictors.
get_deviance() now works for glmerMod, MixMod and glmmTMB models.
The behaviour and documentation of the effects and component arguments, in particular for brmsfit models, were revised to be more consistent.
export_table() now correctly prints the footer if the input was a list of data frames.
Fixed issue (warning) in get_loglikelihood() for binomial models with non-numeric response variables.
find_statistic() correctly distinguishes t- and z-statistic for emmGrid objects.
Fixed issue in model_info() for BGGM and mgcv::gam().
Fixed issue in find_formula() for gamlss models with random() function in formula.
Fixed issue with find_parameters() for brmsfit models when auxiliary parameters are directly modelled.
Fixed issue with get_parameters() and find_parameters() for multi-group blavaan models.
Fixed issue in ellipsis_info() when detecting nested models with poly-terms.
Fixed issue in find_response() for brmsfit models that used the resp_thres() function in the model formula.
Fixed issue in get_predicted_ci() for models with rank-deficient model matrix.
Argument zap_small in format_value() did not work properly over vectorized vectors.
get_predicted() has be revamped with a new API and a stable output form (a vector). In the course of this revision, a new function get_predicted_ci() to calculate uncertainty intervals for model predictions.
Improved support for orm (rms).
svy_vglm (svyVGAM), mjoint (joineRML), mhurdle (mhurdle), sarlm (spatialreg), model_fit (tidymodels)is_gam_model() as a small helper to check if a model is a generalized additive model with smooth terms.Added iterations argument to get_predicted() to control the number of draws returned for Bayesian models.
model_info() now returns $is_gam if model is generalized additive model with smooth terms.
format_table() and export_table() now check for valid input (e.g., non-empty data frame) and give an informative message.
Improved support for MixMod (GLMMadaptive) in get_variance().
Improved print_parameters(), to allow more flexibility and better cope with different output formats.
get_parameters(), find_parameters() and clean_parameters() for emmGrid and emm_list objects were revised and now better match the actual parameter names (also for contrasts).
Fixed issue in get_variance() for models without intercept.
Fixed labelling issue in get_parameters() and clean_parameters() for blavaan models.
clean_parameters() for MCMCglmm objects did not include random parameters.
Fixed minor issue with unintended sub-titles for print_html().
Fixed issue in get_prior() for rstanarm::R2() priors.
elm, eglm (eflm)get_residuals(..., weighted = TRUE) doesn’t throw warnings if weights are 1 (no weights specified).
n_parameters() gains a only_estimable argument, to remove non-estimable parameters from counting the number of parameters for models with rank-deficient model matrix.
format_ci() also gains a zap_small argument.
Fix or disable failing tests on Mac OS.
Fixed issues in get_variance() with non-correlated random-slope-intercepts for lme4 models.
crr (cmprsk), ergm (ergm), btergm (btergm), Rchoice (Rchoice), garch (tseries)Slightly improved handling of different CI-columns in format_table().
model_info() now returns $is_leventest if model is an object returned by car::leveneTest().
get_parameters() supports htest objects.
get_varcov() did not properly remove NA from rank-deficient models.
Fixed issue/warning in get_data() for some htest objects, where the environment was not properly evaluated.
Fixed issue in format_table() with p-value formatting, when input data frame contained a column named "p", which was not numeric.
(Hopefully) fixed issue with failing CRAN checks.
format_table() is an alias for parameters_table(), and is no longer referring to export_table().coxr (coxrobust), coeftest (lmtest), ivFixed (ivFixed), ivprobit (ivprobit), riskRegression (riskRegression). summary.lm, lmodel2 (lmodel2), improved support for bamlss (bamlss).Added get_deviance() function that returns the model deviance as a robust alternative to stats::deviance().
Added model_name() function that returns the model’s “name”.
Added format() method for find_formula() output to flatten it.
Added null_as_ones = TRUE argument to get_weights() to return vector of 1s instead of NULL.
Added get_intercept() as a helper function to easily retrieve the value at the intercept.
Added get_df() as a robust alternative to stats::df.residuals().
Added get_predicted() as a robust alternative to stats::fitted().
Added get_loglikelihood() (and its alias loglikelihood()) function as a robust alternative to stats::logLik().
Added get_residuals() as a robust alternative extract model residuals.
Added ellipsis_info() to specify the nature of ellipsis (...) inputs.
Added is_nested_models() to check if multiple regression models are nested (decreasing or increasing).
Added generic print_html(), to allow other packages to create tables in HTML format (via export_table()) when not printing the output to console.
Added is_mixed_model(), to safely check if a model is a mixed effects model. This function also works for multivariate response models.
n_parameters() was moved from parameters to insight.
find_formula(), find_predictor(), find_random() and related functions now also return names of random effects from generalized additive mixed models (gamm, gamm4, stan_gamm4).
Added support for more BFBayesFactor objects.
model_info() now returns $is_xtab for chisq.test() and BayesFactor::contingencyTableBF(). Furthermore, the $family element for those objects is set to "categorical".
n_obs() now handles number of observations from models with binomial family correctly when these have matrix-columns as response variable.
Fixed issue in find_statistic() for fixest models, which did not return the correct value "t-statistic" for feols().
Fixes inconsistencies in get_priors() for (linear) BFBayesFactor models.
print_color() now use warning(), to better suppress warning messages if required.find_smooth(), to return in particular smooth terms used in a model.get_variance() and get_variance_random() gain a tolerance-argument, to set the tolerance level for singularity checks when computing random effect variances.
parameters_table() formats more objects from the easystats packages, like ROPE-range or p_rope().
find_statistic() now supports models of class scam.
get_data() now also supports htest-object, where possible.
Fix CRAN check issues.
find_formula() for stan_gamm4() now correctly includes random effects.
model_info() now also detects models from oneway.test(), binom.test() chisq.test(), mcnemar.test() and prop.test(). Furthermore, model_info() better deals with objects from BFBayesFactor, and censored regression models no longer return TRUE for $is_linear.
format_table() is going to be renamed in a future update. Please use its alias export_table().
scam (scam), meta_random and meta_fixed (metaBMA), Glm (rms), ridgelm (MASS), mediate (mediation). Partial support for mcmc.list (e.g. bayesGARCH)parameters_table(), which was moved from package parameters to insight. Note that this function is going to be renamed into format_table() in a future update.
find_offset(), to find the name of offset-terms.
Added generics for display() and print_md(), to allow other packages to create tables in other formats when not printing the output to console.
standardize_names() tries to be as loyal to the broom-naming conventions as possible.
The function of the brackets-argument in format_ci() was changed. It is now also possible to provide a length-two character vector, to define own brackets that encompass the CI-values.
Related to the change in format_ci(), the function of the brackets-argument in parameters_table() was changed accordingly. Furthermore, parameters_table() gains a preserve_attributes-argument, to preserve any attributes from the input data frame.
export_table() gains several new arguments that allows to create tables in markdown-format.
print_parameters() gains a keep_parameter_column-argument, to keep (default) both the "Cleaned_Parameter" and "Parameter" columns, or - if FALSE - use "Cleaned_Parameter" as new "Parameter" column.
get_data()Fixed issue in get_data() for MixMod objects, which were caused due to internal changes in GLMMadaptive.
get_data() for zero-inflated models from pscl did not include the offset-term in cases where the offset was defined as argument, not inside the model formula.
Fixed issue in get_data() for coxph models with survival-objects with event-argument as response.
Fixed edge case in get_data() for column name of response values that were log-transformed using log(x+1).
Fixed issue with survreg models that included strata() in their formula.
Fixed warning in CRAN checks for forthcoming R-devel.
get_sigma() to return the residual standard deviation.
standardize_names(), which was moved from package parameters to insight.
maov (stats), HLfit (spaMM), preliminary support for margins (margins), merModList (merTools).Better support for (weighted) multivariate response models of class mlm for functions like get_varcov() or clean_parameters().
Make find_formula() work with t-tests from BayesFactor.
Improved handling for mira objects.
format_bf() gains a na_reference argument, to set the “reference” for Bayes factor values that are NA, and an exact argument for returning scientific formatted extreme values.
format_value() gains a zap_small argument, to prevent scientific printing of numbers if these have more decimal places than indicated by digits.
get_weights() now also returns NULL when all weights were 1.
get_parameters() for BFBayesFactor objects gets a verbose argument.
get_parameters() for emmGrid and emm_list objects gets a summary argument, to either return the full posterior samples or the summarized centrality indices for Bayesian models.
find_formula() for MuMIn::model.avg() now tries to retrieve the random effects part of a formula, when present.
get_weights() gains a na_rm argument to remove possible missing values.
Fix issues with one-sample Bayesian t-tests ( https://github.com/easystats/parameters/issues/297 ).
Fix issue in format_value() that printed "100%" as "1e+02%".
Removed unnecessary white-spaces in format_ci() when upper or lower interval was larger than 1e+5.
has_intercept() did not work correctly when intercept was removed from formula using -1.
find_terms() now shows removal of intercept formula using -1 as term "-1".
Fix issues with get_statistic() for vgam models.
get_data() now works for models from afex_aov().
get_parameters() returns a more informative message for BFBayesFactor objects when not the first model is indexed.
clean_names() now also removes exp()-pattern.
clean_names() for character-objects now works with “interaction patterns” (like clean_names("scale(a):scale(b)")).
format_bf() gains a protect_ratio argument, to print numbers smaller than 1 as ratios.
Fix issues in CRAN checks.
get_priors() now works for more complex BFBayesFactor objects that have multiple custom priors.
get_data() did not always “back-transform” log-transformed or scaled variables to return the original values. Now this bug has been fixed, and get_data() should return all variables on the original scale (as if these variables were not transformed), as stated in the docs.get_data() now returns the correct original data for “empty” polynomials (i.e. poly(x, 1)).
Fix CRAN check issues due to latest estimatr update.
mipo (mice), lqmm and lqm (lqmm). Preliminary support for semLME (smicd), mle (stats4) and mle2 (bbmle).model_info() returns $is_meta = TRUE for brms-meta-analysis models.
Make find_statistic() work with mgcv::bam().
get_variance() now also support truncated_nbinom2() family from glmmTMB.
Fixed issue with correctly detecting sigma-parameters in find_parameters() for multiple-response brmsfit-models.
Fixed issue with find_formula() for models from stan_nlmer().
Fixed issues with find_terms() when response variable included a namespace, like survival::Surv().
Fixed issues with get_priors() for stanreg models, probably caused by the latest update to rstanarm 2.21.2.
Fixed issues in get_variance() for brmsfit models.
Fixed some issues around crq objects (package quantreg).
BGGM (BGGM), metaplus (metaplus), glht (multcomp), glmm (glmm), improved support for manova (stats)format_bf(), format_pd(), format_p(), format_rope() and format_number() were moved from package parameters to insight.get_variance() now also returns the correlation among random slopes.
get_variance() now also (partially) supports brmsfit models.
get_parameters() for models that return (posterior or simulated) samples of model parameters gains a summary-argument, which - if TRUE - returns a point-estimate (mean of samples) instead of the full samples.
format_p() returns "> .999" for p-values equal to or greater than 0.999.
Fixed issue in find_formula() that did not properly work for models with random effects in formula (in lme4 notation), when random effects were in between fixed effects parts.
get_variance() did not return variance components for random effects for null-models with random slopes.
Fixed issue with get_variance() for lme-models with categorical random slope.
Fixed issue that occurred since R 4.0.0 in find_weights() when function call had no weights-argument.
Fixed issue in get_data() for models with cbind()-response variables and matrix-like variables in the model frame (e.g. when using poly()).
Fixed issues with PROreg::BBmm(), due to changes in latest package update.