parameters 0.8.6

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.

parameters 0.8.5

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

• model_parameters() gets a specific behaviour for brms-meta-analysis models.
• model_parameters() for lavaan and blavaan now also prints self-defined parameters.
• model_parameters() for lavaan and blavaan gains more option for standardized parameters.

Bug fixes

• Fix issue in model_parameters() for coxph.penal models.
• Fix issue in model_parameters.metaplus() with random effects.
• Fix issue in check_heterogeneity() when x was a mixed model.
• Fix issue in check_heterogeneity() for data with missing values.
• Fix issue in dof_ml1() when random-effect terms where character vectors.
• Fix issue in print() method for model_parameters() that printed empty lines for rows with complete missing values. Empty lines are now removed.
• Fix issue in parameters_type() when exp() was used in a model formula.

parameters 0.8.2

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

• Allow threshold to be passed to efa_to_cfa() when the model is from factor_analysis().
• Allow correlation matrix to be passed to factor_analysis().
• Fix CRAN check issues.
• Fix issue in model_parameters() for models with non-estimable parameters or statistics.
• Fix issue in model_parameters() for plm models with only one parameter.
• Fix issue in check_heterogeneity() in case no predictor would cause heterogeneity bias.
• Make sure clubSandwich is used conditionally in all places, to properly pass CRAN checks.

parameters 0.8.0

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.

parameters 0.7.0

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

• parameters_table() and print.parameters_model() now explicitly get arguments to define the digits for decimal places used in output.
• ci(), standard_error(), p_value() and model_parameters() for glmmTMB models now also works for dispersion models.

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().

parameters 0.6.1

General

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

Changes to functions

model_parameters()

• model_parameters() now also transforms standard errors when exponentiate = TRUE.
• model_parameters() for anova() from mixed models can now also compute effect sizes like eta squared.
• model_parameters() for aov() gains a type-argument to compute type-1, type-2 or type-3 sums of squares.
• model_parameters() for Bayesian models gains a standardize argument, to return standardized parameters from the posterior distribution.
• Improved print() method for model_parameters() for nested aov() (repeated measurements).
• You can now control whether demean() should add attributes to indicate within- and between-effects. This is only relevant for the print()-method of model_parameters().

Bug fixes

• Fixed model_parameters() for anova() from lmerTest models.

parameters 0.6.0

Breaking changes

• Alias model_bootstrap() was removed, please use bootstrap_model().
• Alias parameters_bootstrap() was removed, please use bootstrap_parameters().
• Alias model_simulate() was removed, please use simulate_model().
• Alias parameters_simulate() was removed, please use simulate_parameters().
• Alias parameters_selection() was removed, please use select_parameters().
• Alias parameters_reduction() was removed, please use reduce_parameters().
• Functions DDR(), ICA() and cmds() are no longer exported, as these were intended to be used internally by reduce_parameters() only.
• skewness() and kurtosis() always return a data frame.

New supported models

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

Changes to functions

model_parameters()

• Improved print-method for model_parameters.brmsfit().
• Improved print-method for model_parameters.merMod() when fitting REWB-Models (see demean()).
• Improved efficiency for model_parameters() (for linear mixed models) when df_method = "kenward".
• model_parameters() gets a p_adjust-argument, to adjust p-values for multiple comparisons.
• Minor improvements for cluster_analysis() when method = "kmeans" and force = TRUE (factors now also work for kmeans-clustering).

p_value(), ci() and standard_error()

• p_value_kenward(), se_kenward() etc. now give a warning when model was not fitted by REML.
• Added ci(), standard_error() and p_value() for lavaan and blavaan objects.
• Added standard_error() for brmsfit and stanreg objects.

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.

parameters 0.5.0

Breaking changes

• skewness() now uses a different method to calculate the skewness by default. Different methods can be selected using the type-argument.
• kurtosis() now uses a different method to calculate the skewness by default. Different methods can be selected using the type-argument.

New supported models

• Added support for cglm (cglm), DirichletRegModel (DirichletReg)

General

• Added new vignettes on ‘Standardized Model Parameters’ and ‘Robust Estimation of Standard Errors’, and vignettes are now also published on CRAN.
• Improved handling of robust statistics in model_parameters(). This should now work for more models than before.
• Improved accuracy of ci.merMod() for method = "satterthwaite" and method = "kenward".
• select_parameters() for stanreg models, which was temporarily removed due to the CRAN removal of package projpred, is now re-implemented.

New functions

• dof_betwithin() to compute degrees of freedom based on a between-within approximation method (and related to that, p_value_*() and se_*() for this method were added as well).
• random_parameters() that returns information about the random effects such as variances, R2 or ICC.
• closest_component() as a small helper that returns the component index for each variable in a data frame that was used in principal_components().
• get_scores() as a small helper to extract scales and calculate sum scores from a principal component analysis (PCA, principal_components()).

Changes to functions

• n_clusters() gets the option "M3C" for the package-argument, so you can try to determine the number of cluster by using the M3C::M3C() function.
• The print()-method for model_parameters() gets a select-argument, to print only selected columns of the parameters table.
• model_parameters() for meta-analysis models has an improved print()-method for subgroups (see examples in ?model_parameters.rma).
• model_parameters() for mixed models gets a details-argument to additionally print information about the random effects.
• model_parameters() now accepts the df_method-argument for more (mixed) models.
• The Intercept-parameter in model_parameters() for meta-analysis models was renamed to "Overall".
• skewness() gets a type-argument, to compute different types of skewness.
• kurtosis() gets a type-argument, to compute different types of skewness.
• describe_distribution() now also works on data frames and gets a nicer print-method.

Bug fixes

• Fixed issue in model_parameters() when robust = TRUE, which could sometimes mess up order of the statistic column.
• Fixed issues in model_parameters() with wrong df for lme-models.
• Fixed issues in model_parameters.merMod() when df_method was not set to default.
• Fixed issues in model_parameters.merMod() and model_parameters.gee() when robust = TRUE.
• Fixed issues with coxph models with only one parameter.
• Fixed issue in format_p() when argument digits was "apa".
• Fixed issues in model_parameters() for zeroinfl-models.

parameters 0.4.1

Bug fixes

• Fix CRAN check issues, caused by removal of package ‘projpred’.