General

Changes to functions

  • model_parameters() for merMod models now also computes CIs for the random SD parameters when ci_method="boot" (previously, this was only possible when ci_method was "profile").

  • model_parameters() for glmmTMB models now computes CIs for the random SD parameters. Note that these are based on a Wald-z-distribution.

  • Similar to model_parameters.htest(), the model_parameters.BFBayesFactor() method gains cohens_d and cramers_v arguments to control if you need to add frequentist effect size estimates to the returned summary dataframe. Previously, this was done by default.

Bug fixes

  • Fixed bug with ci() for class merMod when method="boot".

  • Fixed issue with correct association of components for ordinal models of classes clm and clm2.

  • Fixed issues in random_parameters() and model_parameters() for mixed models without random intercept.

  • Confidence intervals for random parameters in model_parameters() failed for (some?) glmer models.

Breaking changes

Note that these functions will be removed in the next release of parameters package and they are currently being re-exported only as a convenience for the package developers. This release should provide them with time to make the necessary changes before this breaking change is implemented.

General

  • The handling to approximate the degrees of freedom in model_parameters(), ci() and p_value() was revised and should now be more consistent. Some bugs related to the previous computation of confidence intervals and p-values have been fixed. Now it is possible to change the method to approximate degrees of freedom for CIs and p-values using the ci_method, resp. method argument. This change has been documented in detail in ?model_parameters, and online here: https://easystats.github.io/parameters/reference/model_parameters.html

  • Minor changes to print() for glmmTMB with dispersion parameter.

  • Added vignette on printing options for model parameters.

Changes to functions

model_parameters()

  • The df_method argument in model_parameters() is deprecated. Please use ci_method now.

  • model_parameters() with standardize = "refit" now returns random effects from the standardized model.

  • model_parameters() and ci() for lmerMod models gain a "residuals" option for the ci_method (resp. method) argument, to explicitly calculate confidence intervals based on the residual degrees of freedom, when present.

  • model_parameters() supports following new objects: trimcibt, wmcpAKP, dep.effect (in WRS2 package), systemfit

  • model_parameters() gains a new argument table_wide for ANOVA tables. This can be helpful for users who may wish to report ANOVA table in wide format (i.e., with numerator and denominator degrees of freedom on the same row).

  • model_parameters() gains two new arguments, keep and drop. keep is the new names for the former parameters argument and can be used to filter parameters. While keep selects those parameters whose names match the regular expression pattern defined in keep, drop is the counterpart and excludes matching parameter names.

  • When model_parameters() is called with verbose = TRUE, and ci_method is not the default value, the printed output includes a message indicating which approximation-method for degrees of freedom was used.

  • model_parameters() for mixed models with ci_method = "profile computes (profiled) confidence intervals for both fixed and random effects. Thus, ci_method = "profile allows to add confidence intervals to the random effect variances.

  • model_parameters() should longer fail for supported model classes when robust standard errors are not available.

Other functions

  • n_factors() the methods based on fit indices have been fixed and can be included separately (package = "fit"). Also added a n_max argument to crop the output.

  • compare_parameters() now also accepts a list of model objects.

  • describe_distribution() gets verbose argument to toggle warnings and messages.

  • format_parameters() removes dots and underscores from parameter names, to make these more “human readable”.

  • The experimental calculation of p-values in equivalence_test() was replaced by a proper calculation p-values. The argument p_value was removed and p-values are now always included.

  • Minor improvements to print(), print_html() and print_md().

Bug fixes

  • The random effects returned by model_parameters() mistakenly displayed the residuals standard deviation as square-root of the residual SD.

  • Fixed issue with model_parameters() for brmsfit objects that model standard errors (i.e. for meta-analysis).

  • Fixed issue in model_parameters for lmerMod models that, by default, returned residual degrees of freedom in the statistic column, but confidence intervals were based on Inf degrees of freedom instead.

  • Fixed issue in ci_satterthwaite(), which used Inf degrees of freedom instead of the Satterthwaite approximation.

  • Fixed issue in model_parameters.mlm() when model contained interaction terms.

  • Fixed issue in model_parameters.rma() when model contained interaction terms.

  • Fixed sign error for model_parameters.htest() for objects created with t.test.formula() (issue #552)

  • Fixed issue when computing random effect variances in model_parameters() for mixed models with categorical random slopes.

Breaking changes

New supported model classes

  • SemiParBIV (GJRM), selection (sampleSelection), htest from the survey package, pgmm (plm).

General

  • Performance improvements for models from package survey.

New functions

Changes to functions

model_parameters()

other

  • bootstrap_models() for merMod and glmmTMB objects gains further arguments to set the type of bootstrapping and to allow parallel computing.

  • bootstrap_parameters() gains the ci_method type "bci", to compute bias-corrected and accelerated bootstrapped intervals.

  • ci() for svyglm gains a method argument.

Bug fixes

General

New supported model classes

  • blrm (rmsb), AKP, med1way, robtab (WRS2), epi.2by2 (epiR), mjoint (joineRML), mhurdle (mhurdle), sarlm (spatialreg), model_fit (tidymodels), BGGM (BGGM), mvord (mvord)

Changes to functions

model_parameters()

  • model_parameters() for blavaan models is now fully treated as Bayesian model and thus relies on the functions from bayestestR (i.e. ROPE, Rhat or ESS are reported) .

  • The effects-argument from model_parameters() for mixed models was revised and now shows the random effects variances by default (same functionality as random_parameters(), but mimicking the behaviour from broom.mixed::tidy()). When the group_level argument is set to TRUE, the conditional modes (BLUPs) of the random effects are shown.

  • model_parameters() for mixed models now returns an Effects column even when there is just one type of “effects”, to mimic the behaviour from broom.mixed::tidy(). In conjunction with standardize_names() users can get the same column names as in tidy() for model_parameters() objects.

  • model_parameters() for t-tests now uses the group values as column names.

  • print() for model_parameters() gains a zap_small argument, to avoid scientific notation for very small numbers. Instead, zap_small forces to round to the specified number of digits.

  • To be internally consistent, the degrees of freedom column for lqm(m) and cgam(m) objects (with t-statistic) is called df_error.

  • model_parameters() gains a summary argument to add summary information about the model to printed outputs.

  • Minor improvements for models from quantreg.

  • model_parameters supports rank-biserial, rank epsilon-squared, and Kendall’s W as effect size measures for wilcox.test(), kruskal.test, and friedman.test, respectively.

Other functions

Bug fixes

General

  • Roll-back R dependency to R >= 3.4.

  • Bootstrapped estimates (from bootstrap_model() or bootstrap_parameters()) can be passed to emmeans to obtain bootstrapped estimates, contrasts, simple slopes (etc) and their CIs.

    • These can then be passed to model_parameters() and related functions to obtain standard errors, p-values, etc.

Breaking changes

  • model_parameters() now always returns the confidence level for as additional CI column.

  • The rule argument in equivalenct_test() defaults to "classic".

New supported model classes

  • crr (cmprsk), leveneTest() (car), varest (vars), ergm (ergm), btergm (btergm), Rchoice (Rchoice), garch (tseries)

New functions

Changes to functions

  • Estimation of bootstrapped p-values has been re-written to be more accurate.

  • model_parameters() for mixed models gains an effects-argument, to return fixed, random or both fixed and random effects parameters.

  • Revised printing for model_parameters() for metafor models.

  • model_parameters() for metafor models now recognized confidence levels specified in the function call (via argument level).

  • Improved support for effect sizes in model_parameters() from anova objects.

Bug fixes

  • Fixed edge case when formatting parameters from polynomial terms with many degrees.

  • Fixed issue with random sampling and dropped factor levels in bootstrap_model().

New supported model classes

  • coxr (coxrobust), coeftest (lmtest), ivfixed (ivfixed), ivprobit (ivprobit), riskRegression (riskRegression), fitdistr (MASS), yuen, t1way, onesampb, mcp1 and mcp2 (WRS2), Anova.mlm (car), rqs (quantreg), lmodel2 (lmodel2), summary.lm, PMCMR, osrt and trendPMCMR (PMCMRplus), bamlss (bamlss).

New functions

Printing and table Formatting

  • print_html() as an alias for display(format = "html"). This allows to print tabular outputs from data frames (as returned by most functions in parameters) into nicely rendered HTML markdown tables.

Changes to functions

  • Added more effect size measures to model_parameters() for htest objects.

  • model_parameters() for anova objects gains a power argument, to calculate the power for each parameter.

  • ci() for models from lme4 and glmmTMB can now computed profiled confidence intervals, using method = "profile". Consequently, model_parameters() with df_method = "profile" also computes profiled confidence intervals. For models of class glmmTMB, option "uniroot" is also available.

Bug fixes

  • model_parameters() for t-tests when standardize_d = TRUE, did not return columns for the group-specific means.

  • Fixed issue in p_value() for fixest::feols().

  • Fixed issue in model_parameters() for glmer() models with p-values that were calculated with df_method = "ml1" or df_method = "betwithin".

  • Fixed issue in model_parameters() for multinomial models when response was a character vector (and no factor).

  • Fixed issue in print_md() for model-parameters objects from Bayesian models.

  • Fixed issues with printing of model parameters for multivariate response models from brms.

  • Fixed issue with paired t-tests and model_parameters().

New functions

Bug fixes

  • Fixed breaking code / failing tests due to latest effectsize update.

  • Fixed issue with model_parameters() for models of class mlm.

  • Undocumented arguments digits, ci_digits and p_digits worked for print(), but not when directly called inside model_parameters(). Now, model_parameters(model, digits = 5, ci_digits = 8) works again.

  • Fixed some minor printing-issues.

Breaking changes

  • The default-method for effect sizes in model_parameters() for Anova-models (i.e. when arguments omega_squared, eta_squared or epsilon_squared are set to TRUE) is now "partial", as initially intended.

  • Column names for degrees of freedom were revised. "df_residual" was replaced by the more generic "df_error". Moreover, models of class htest now also have the column name "df_error" and no longer "df" (where applicable).

  • Some re-exports for functions that were moved to insight longer ago, were now removed.

New supported model classes

New functions

Printing and table Formatting

  • display(), to format output from package-functions into different formats.

  • print_md() as an alias for display(format = "markdown"). This allows to print tabular outputs from data frames (as returned by most functions in parameters) into nicely rendered markdown tables.

  • format(), to create a “pretty data frame” with nicer column names and formatted values. This is one of the worker-functions behind print() or print_md().

Changes to functions

model_parameters()

  • model_parameters() for Anova-models (of class aov, anova etc.) gains a ci-argument, to add confidence intervals to effect size parameters.

  • model_parameters() for htest objects gains a cramers_v and phi argument, to compute effect size parameters for objects from chisq.test(), and a standardized_D argument, to compute effect size parameters for objects from t.test().

  • model_parameters() for metafor-models is more stable when called from inside functions.

  • model_parameters() for metaBMA-models now includes prior information for the meta-parameters.

  • model_parameters() for meta-analysis-models gains a include_studies-argument, to include or remove studies from the output.

  • model_parameters() for gam-models now includes the residual df for smooth terms, and no longer the reference df.

  • Slightly revised and improved the print() method for model_parameters().

Other functions

  • describe_distribution() now includes the name of the centrality index in the CI-column, when centrality = "all".

  • pool_parameters() gains a details-argument. For mixed models, and if details = TRUE, random effect variances will also be pooled.

Bug fixes

New supported model classes

  • Support for maov (stats), HLfit (spaMM), scam (scam), preliminary support for emm_list (emmeans), merModList (merTools), meta_random, meta_bma and meta_fixed (metaBMA).

New functions

General

Changes to functions

Printing model parameters

  • print() for model_parameters() now names the coefficients column depending on the model type (i.e. "Odds Ratios" for logistic regression when exponentiate = TRUE etc.)

  • print() for model_parameters() gains a show_sigma argument, to show or hide information on the residual standard deviation.

  • print() for model_parameters() displays a message for Bayesian models, indicating which method to compute credible intervals was used.

Other changes

  • data_partition() gets a seed argument, to explicitly set the seed before random sampling of test and training data.

  • Revised parameters_table(), to improve readability of printed output.

Bug fixes

  • Fixed issues in model_parameters() for vgam and mira objects.

  • Fixed issue where model_parameters() for emmGrid objects falsely removed the Coefficient column.

  • Fixed issue in parameters_type() for factors with different effects-coding than treatment contrasts.

  • Fixed issues due to latest effectsize update.

Bug fixes

  • Fixed issues with glmmTMB models with dispersion-parameter.

  • Fixed issue where model_parameters() for glmmTMB models falsely removed the Component column.

  • Fixed issue with missing CI columns in model_parameters() when standardize was one of the options except "refit".

  • parameters_type() did not correctly detect interaction terms for specific patterns like scale() included in the interaction.

General

  • Added vignette on model parameters and missing data.

  • Update citation.

New supported model classes

  • Support for mipo (mice), lqm and lqmm (lqmm). Preliminary support for semLME (smicd), mle2 (bbmle), mle (stats4)

  • model_parameters() for objects of class mira (mice).

Changes to functions

Bug fixes

New supported models

  • metaplus (metaplus), glht (multcomp), glmm (glmm), manova (stats), crq and crqs (quantreg)

  • Improved support for models from the rms package.

Changes to functions

  • Improved parameters formatting for ordered factors in model_parameters() (and format_parameters()).

  • Argument df_method can now also be applied to GLMs, to allow calculation of confidence intervals based on Wald-approximation, not profiled confidence intervals. This speeds up computation of CIs for models fit to large data sets.

  • Improved select_parameters() for mixed models, and revised docs and associated vignette.

Bug fixes

New supported models

  • robmixglm (robmixglm), betaor, betamfx, logitor, poissonirr, negbinirr, logitmfx, probitmfx, poissonmfx, negbinmfx (mfx), partial support emmGrid (emmeans)

Changes to functions

simulate_parameters() and simulate_model()

  • has a nicer print() method.

  • now also simulate parameters from the dispersion model for glmmTMB objects.

  • gets a verbose argument, to show or hide warnings and messages.

Bug fixes

  • fix issue with rank deficient models.

General

  • We changed the computation of confidence intervals or standard errors, so these are now based on a t-distribution with degrees of freedom and not normal distribution assuming infinite degrees of freedom. This was implemented for most functions before and only affects few functions (like equivalence_test() or CIs for standardized parameters from model_parameters() when standardization method was "posthoc").

New supported models

  • averaging (MuMIn), bayesx (R2BayesX), afex_aov (afex)

New functions

  • check_heterogeneity() as a small helper to find variables that have a within- and between-effect related to a grouping variable (and thus, may result in heterogeneity bias, see this vignette).

Changes to functions

equivalence_test()

  • gains a rule argument, so equivalence testing can be based on different approaches.

  • for mixed models gains an effect argument, to perform equivalence testing on random effects.

  • gains a p_values argument, to calculate p-values for the equivalence test.

  • now supports more frequentist model objects.

describe_distribution()

  • now works on grouped data frames.

  • gains ci and iterations arguments, to compute confidence intervals based on bootstrapping.

  • gains a iqr argument, to compute the interquartile range.

  • SE column was removed.

model_parameters()

  • model_parameters() for Stan-models (brms, rstanarm) gains a group_level argument to show or hide parameters for group levels of random effects.

  • Improved accuracy of confidence intervals in model_parameters() with standardize = "basic" or standardize = "posthoc".

  • model_parameters.merMod() no longer passes ... down to bootstrap-functions (i.e. when bootstrap = TRUE), as this might conflict with lme4::bootMer().

  • For ordinal models (like MASS::polr() or ordinal::clm()), a Component column is added, indicating intercept categories ("alpha") and estimates ("beta").

  • The select-argument from print.parameters_model() now gets a "minimal"-option as shortcut to print coefficients, confidence intervals and p-values only.

Other changes

Bug fixes

  • Fixed issue in equivalence_test() for mixed models.

  • Fixed bug for model_parameters.anova(..., eta_squared = "partial") when called with non-mixed models.

  • Fixed issue with wrong degrees of freedom in model_parameters() for gam models.

  • Fixed issue with unused arguments in model_parameters().

General

  • Remove ‘Zelig’ from suggested packages, as it was removed from CRAN.

Changes to functions

model_parameters()

Bug fixes

Breaking changes

New supported models

  • Added support for arima (stats), bife (bife), bcplm and zcpglm (cplm)

Changes to functions

model_parameters()

p_value(), ci() and standard_error()

Other changes

  • Run certain tests only locally, to reduce duration of CRAN checks.

  • skewness(), kurtosis() and smoothness() get an iteration argument, to set the numbers of bootstrap replicates for computing standard errors.

  • Improved print-method for factor_analysis().

  • demean() now additionally converts factors with more than 2 levels to dummy-variables (binary), to mimic panelr-behaviour.

Bug fixes

  • Fixed minor issue with the print()-method for model_parameters.befa().

  • Fixed issues in model_parameters() (for linear mixed models) with wrong order of degrees of freedom when df_method was different from default.

  • Fixed issues in model_parameters() (for linear mixed models) with accuracy of p-values when df_method = "kenward.

  • Fixed issues in model_parameters() with wrong test statistic for lmerModLmerTest models.

  • Fixed issue in format_parameters() (which is used to format output of model_parameters()) for factors, when variable name was also part of factor levels.

  • Fixed issue in degrees_of_freedem() for logistf-models, which unintentionally printed the complete model summary.

  • Fixed issue in model_parameters() for mlm models.

  • Fixed issue in random_parameters() for uncorrelated random effects.