- Following models/objects are now supported by model-information functions like
`model_family()`

,`link_inverse()`

or`model_frame()`

:`MixMod`

(package**GLMMadaptive**),**MCMCglmm**,`mlogit`

and`gmnl`

. - Reduce package dependencies.

`cred_int()`

, to compute uncertainty intervals of Bayesian models. Mimics the behaviour and style of`hdi()`

and is thus a convenient complement to functions like`posterior_interval()`

.

`equi_test()`

now finds better defaults for models with binomial outcome (like logistic regression models).`r2()`

for mixed models now also should work properly for mixed models fitted with**rstanarm**.`anova_stats()`

and alike (e.g.`eta_sq()`

) now all preserve original term names.`model_family()`

now returns`$is_count = TRUE`

, when model is a count-model, and`$is_beta = TRUE`

for models with beta-family.`pred_vars()`

checks that return value has only unique values.`pred_vars()`

gets a`zi`

-argument to return the variables from a model’s zero-inflation-formula.

- Fix minor issues in
`wtd_sd()`

and`wtd_mean()`

when weight was`NULL`

(which usually shoudln’t be the case anyway). - Fix potential issue with
`deparse()`

, cutting off very long formulas in various functions. - Fix encoding issues in help-files.

- Export
`dplyr::n()`

, to meet forthcoming changes in dplyr 0.8.0.

`boot_ci()`

gets a`ci.lvl`

-argument.- The
`rotation`

-argument in`pca_rotate()`

now supports all rotations from`psych::principal()`

. `pred_vars()`

gets a`fe.only`

-argument to return only fixed effects terms from mixed models, and a`disp`

-argument to return the variables from a model’s dispersion-formula.`icc()`

for Bayesian models gets a`adjusted`

-argument, to calculate adjusted and conditional ICC (however, only for Gaussian models).- For
`icc()`

for non-Gaussian Bayes-models, a message is printed that recommends setting argument`ppd`

to`TRUE`

. `resp_val()`

and`resp_var()`

now also work for**brms**-models with additional response information (like`trial()`

in formula).`resp_var()`

gets a`combine`

-argument, to return either the name of the matrix-column or the original variable names for matrix-columns.`model_frame()`

now also returns the original variables for matrix-column-variables.`model_frame()`

now also returns the variable from the dispersion-formula of**glmmTMB**-models.`model_family()`

and`link_inverse()`

now supports**glmmPQL**,**felm**and**lm_robust**-models.`anova_stats()`

and alike (`omeqa_sq()`

etc.) now support gam-models from package**gam**.`p_value()`

now supports objects of class`svyolr`

.

- Fix issue with
`se()`

and`get_re_var()`

for objects returned by`icc()`

. - Fix issue with
`icc()`

for Stan-models. `var_names()`

did not clear terms with log-log transformation, e.g.`log(log(y))`

.- Fix issue in
`model_frame()`

for models with splines with only one column.

- Revised help-files for
`r2()`

and`icc()`

, also by adding more references.

`re_grp_var()`

to find group factors of random effects in mixed models.

`omega_sq()`

and`eta_sq()`

give more informative messages when using non-supported objects.`r2()`

and`icc()`

give more informative warnings and messages.`tidy_stan()`

supports printing simplex parameters of monotonic effects of**brms**models.`grpmean()`

and`mwu()`

get a`file`

and`encoding`

argument, to save the HTML output as file.

`model_frame()`

now correctly names the offset-columns for terms provided as`offset`

-argument (i.e. for models where the offset was not specified inside the formula).- Fixed issue with
`weights`

-argument in`grpmean()`

when variable name was passed as character vector. - Fixed issue with
`r2()`

for**glmmTMB**models with`ar1`

random effects structure.

`wtd_chisqtest()`

to compute a weighted Chi-squared test.`wtd_median()`

to compute the weighted median of variables.`wtd_cor()`

to compute weighted correlation coefficients of variables.

`mediation()`

can now cope with models from different families, e.g. if the moderator or outcome is binary, while the treatment-effect is continuous.`model_frame()`

,`link_inverse()`

,`pred_vars()`

,`resp_var()`

,`resp_val()`

,`r2()`

and`model_family()`

now support`clm2`

-objects from package**ordinal**.`anova_stats()`

gives a more informative message for non-supported models or ANOVA-options.

- Fixed issue with
`model_family()`

and`link_inverse()`

for models fitted with`pscl::hurdle()`

or`pscl::zeroinfl()`

. - Fixed issue with wrong title in
`grpmean()`

for grouped data frames, when grouping variable was an unlabelled factor. - Fix issue with
`model_frame()`

for**coxph**-models with polynomial or spline-terms. - Fix issue with
`mediation()`

for logical variables.

- Reduce package dependencies.

`wtd_ttest()`

to compute a weighted t-test.`wtd_mwu()`

to compute a weighted Mann-Whitney-U or Kruskal-Wallis test.

`robust()`

was revised, getting more arguments to specify different types of covariance-matrix estimation, and handling these more flexible.- Improved
`print()`

-method for`tidy_stan()`

for*brmsfit*-objects with categorical-families. `se()`

now also computes standard errors for relative frequencies (proportions) of a vector.`r2()`

now also computes r-squared values for*glmmTMB*-models from`genpois`

-families.`r2()`

gives more precise warnings for non-supported model-families.`xtab_statistics()`

gets a`weights`

-argument, to compute measures of association for contingency tables for weighted data.- The
`statistics`

-argument in`xtab_statistics()`

gets a`"fisher"`

-option, to force Fisher’s Exact Test to be used. - Improved variance calculation in
`icc()`

for generalized linear mixed models with Poisson or negative binomial families. `icc()`

gets an`adjusted`

-argument, to calculate the adjusted and conditional ICC for mixed models.- To get consistent argument names accross functions, argument
`weight.by`

is now deprecated and renamed into`weights`

.

- Fix issues with effect size computation for repeated-measure Anova when using bootstrapping to compute confidence intervals.
`grpmean()`

now also adjusts the`n`

-columm for weighted data.`icc()`

,`re_var()`

and`get_re_var()`

now correctly compute the random-effect-variances for models with multiple random slopes per random effect term (e.g.,`(1 + rs1 + rs2 | grp)`

).- Fix issues in
`tidy_stan()`

,`mcse()`

,`hdi()`

and`n_eff()`

for`stan_polr()`

-models. - Plotting
`equi_test()`

did not work for intercept-only models.

- The S3-generics for functions like
`hdi()`

,`rope()`

,`equi_test()`

etc. are now more generic, and function usage for each supported object is now included in the documentation. - Following functions are now S3-generic:
`icc()`

,`r2()`

,`p_value()`

,`se()`

, and`std_beta()`

. - Added
`print()`

-methods for some more functions, for a clearer output. - Revised
`r2()`

for mixed models (packages**lme4**,**glmmTMB**). The r-squared value should be much more precise now, and reports the marginal and conditional r-squared values. - Reduced package dependencies and removed
*apaTables*and*MBESS*from suggested packages `stanmvreg`

-models are now supported by many functions.

`binned_resid()`

to plot binned residuals for logistic regression models.`error_rate()`

to compute model quality for logistic regression models.`auto_prior()`

to quickly create automatically adjusted priors for brms-models.`difficulty()`

to compute the item difficulty.

`icc()`

gets a`ppd`

-argument for Stan-models (*brmsfit*and*stanreg*), which performs a variance decomposition based on the posterior predictive distribution. This is the recommended way for non-Gaussian models.- For Stan-models (
*brmsfit*and*stanreg*),`icc()`

now also computes the HDI for the ICC and random-effect variances. Use the`prob`

-argument to specify the limits of this interval. `link_inverse()`

and`model_family()`

now support*clmm*-models (package*ordinal*) and*glmRob*and*lmRob*-models (package*robust*).`model_family()`

gets a`multi.resp`

-argument, to return a list of family-informations for multivariate-response models (of class`brmsfit`

or`stanmvreg`

).`link_inverse()`

gets a`multi.resp`

-argument, to return a list of link-inverse-functions for multivariate-response models (of class`brmsfit`

or`stanmvreg`

).`p_value()`

now supports*rlm*-models (package*MASS*).`check_assumptions()`

for single models with`as.logical = FALSE`

now has a nice print-method.`eta_sq()`

and`omega_sq()`

now also work for repeated-measure Anovas, i.e. Anova with error term (requires broom > 0.4.5).

`model_frame()`

and`var_names()`

now correctly cleans nested patterns like`offset(log(x + 10))`

from column names.`model_frame()`

now returns proper column names from*gamm4*models.`model_frame()`

did not work when the model frame had spline-terms and weights.- Fix issue in
`robust()`

when`exponentiate = TRUE`

and`conf.int = FALSE`

. `reliab_test()`

returned an error when the provided data frame has less than three columns, instead of returning`NULL`

.

- Added new Vignette
*Statistics for Bayesian Models*.

`equi_test()`

to test if parameter values in Bayesian estimation should be accepted or rejected.`mediation()`

to print a summary of a mediation analysis from multivariate response models fitted with*brms*.

`link_inverse()`

now also returns the link-inverse function for cumulative-family*brms*-models.`model_family()`

now also returns an`is_ordinal`

-element with information if the model is ordinal resp. a cumulative link model.- Functions that access model information (like
`model_family()`

) now better support`vglm`

-models (package*VGAM*). `r2()`

now also calculates the standard error for*brms*or*stanreg*models.`r2()`

gets a`loo`

-argument to calculate LOO-adjusted rsquared values for*brms*or*stanreg*models. This measure comes conceptionally closer to an adjusted r-squared measure.- Effect sizes (
`anova_stats()`

,`eta_sq()`

etc.) are now also computed for mixed models. - To avoid confusion,
`n_eff()`

now computes the number of effective samples, and no longer its ratio in relation to the total number of samples. - The column name for the ratio of the number of effective samples in
`tidy_stan()`

is now named*neff_ratio*, to avoid confusion.

- Fixed issue in
`se()`

for`icc()`

-objects, where random effect term could not be found. - Fixed issue in
`se()`

for`merMod`

-objects. - Fixed issue in
`p_value()`

for mixed models with KR-approximation, which is now more accurate.

- Remove
*tidyverse*from suggested packages, as requested by maintainers.

`mwu()`

now requires a data frame as first argument, followed by the names of the two variables to perform the Mann-Whitney-U-Test on.

`tidy_stan()`

was improved especially for more complex multilevel models.- Make
`tidy_stan()`

for large`brmsfit`

-objects (esp. with random effects) more efficient. - Better
`print()`

-method for`tidy_stan()`

,`hdi()`

,`rope()`

,`icc()`

and some other functions. `link_inverse()`

now also should return the link-inverse function for most (or some or all?) custom families of*brms*-models.- The
`weight.by`

-arguments in`grpmean()`

and`mwu()`

now should be a variable name from a variable in`x`

, and no longer a separate vector.

`model_family()`

to get model-information about family and link-functions. This function is intended to be “generic” and work with many different model objects, because not all packages provide a`family()`

function.

- Fix issue with
`omega_sq()`

,`eta_sq()`

etc. when confidence intervals were computed with bootstrapping and the model-formula contained function calls like`scale()`

or`as.factor()`

. - Fix issue with
`p_value()`

for unconditional mixed models. - Fix typo in
`xtab_statistics()`

. - Fix issue with wrong calculation of Nagelkerke’s r-squared value in
`r2()`

. - Fix issue for factors with character leves in
`typical_value()`

, when argument`fun`

for factors was set to`mode`

. - Don’t show prior-samples in
`hdi()`

,`tidy_stan()`

etc. for*brmsfit*-objects. - Fixed issues in
`model_frame()`

with spline-terms when missing values were removed due to casewise deletion.

- Revise examples, vignettes and package description to make sure all used packages are available for CRAN checks on operating systems.

`residuals.svyglm.nb()`

as S3-generic`residuals()`

method for objects fitted with`svyglm.nb()`

.

`icc()`

gets a`posterior`

-argument, to compute ICC-values from`brmsfit`

-objects, for the whole posterior distribution.`icc()`

now gives a warning when computed for random-slope-intercept models, to warn user about probably inappropriate inference.`r2()`

now computes Bayesian version of R-squared for`stanreg`

and`brmsfit`

objects.- Argument
`prob`

in`hdi()`

now accepts a vector of scalars to compute HDIs for multiple probability tresholds at once. - Argument
`probs`

in`tidy_stan()`

was renamed into`prob`

, to be consistent with`hdi()`

. `mwu()`

gets an`out`

-argument, to print output to console, or as HTML table in the viewer or web browser.`scale_weights()`

now also works if weights have missing values.`hdi()`

and`rope()`

get`data.frame`

-methods.`omega_sq()`

and`eta_sq()`

get a`ci.lvl`

-argument to compute confidence intervals for the effect size statistics.`omega_sq()`

,`eta_sq()`

and`cohens_f()`

now always return a data frame with at least two columns: term name and effect size. Confidence intervals are added as additional columns, if the`ci.lvl`

-argument is`TRUE`

.`omega_sq()`

gets a`partial`

-argument to compute partial omega-squared.`omega_sq()`

,`eta_sq()`

,`cohens_f()`

and`anova_stats()`

now support`anova.rms`

-objects from the*rms*-package.

- Fix unnecessary warning for tibbles in
`mic()`

. - Make sure that
`model_frame()`

does not return duplicated column names. - Fix issue in
`tidy_stan()`

with incorrect*n_eff*statistics for*sigma*parameter in mixed models. - Fix issue in
`tidy_stan()`

, which did not work when`probs`

was of length greater than 2. - Fix issue in
`icc()`

with*brmsfit*-models, which was broken probably due to internal changes in*brms*.

- Remove unused imports.
- Cross refences from
`dplyr::select_helpers`

were updated to`tidyselect::select_helpers`

.

`var_names()`

now also cleans variable names from variables modeled with the`mi()`

function (multiple imputation on the fly in*brms*).`reliab_test()`

gets an`out`

-argument, to print output to console, or as HTML table in the viewer or web browser.

- Fix issues with
`mcse()`

,`n_eff()`

and`tidy_stan()`

with more complex*brmsfit*-models. - Fix issue in
`typical_value()`

to prevent error for R-oldrel-Windows. `model_frame()`

now returns response values from models, which are in matrix form (bound with`cbind()`

), as is.- Fixed issues in
`grpmean()`

, where values instead of value labels were printed if some categories were not present in the data.

- Beautiful colored output for
`grpmean()`

and`mwu()`

.

`mcse()`

to compute the Monte Carlo standard error for`stanreg`

- and`brmsfit`

-models.`n_eff()`

to compute the effective sample size for`stanreg`

- and`brmsfit`

-models.

`grpmean()`

now uses`contrasts()`

from package*emmeans*to compute p-values, which correclty indicate whether the sub-group mean is significantly different from the total mean.`grpmean()`

gets an`out`

-argument, to print output to console, or as HTML table in the viewer or web browser.`tidy_stan()`

now includes information on the Monte Carlo standard error.`model_frame()`

,`p_value()`

and`link_inverse()`

now support Zelig-relogit-models.`typical_value()`

gets an explicit`weight.by`

-argument.

`model_frame()`

did not work properly for variables that were standardized with`scale()`

.- In certain cases,
`weight.by`

-argument did not work in`grpmean()`

.

- Remove deprecated
`get_model_pval()`

. - Revised documentation for
`overdisp()`

.

`scale_weights()`

to rescale design weights for multilevel models.`pca()`

and`pca_rotate()`

to create tidy summaries of principal component analyses or rotated loadings matrices from PCA.`gmd()`

to compute Gini’s mean difference.`is_prime()`

to check whether a number is a prime number or not.

`link_inverse()`

now supports`brmsfit`

,`multinom`

and`clm`

-models.`p_value()`

now supports`polr`

and`multinom`

-models.`zero_count()`

gets a`tolerance`

-argument, to accept models with a ratio within a certain range of 1.`var_names()`

now also cleans variable names from variables modelled with the`offset()`

,`lag()`

or`diff()`

function.`icc()`

,`re_var()`

and`get_re_var()`

now support`brmsfit`

-objects (models fitted with the*brms*-package).- For
`fun = "weighted.mean"`

,`typical_value()`

now checks if vector of weights is of same length as`x`

. - The print-method for
`grpmean()`

now also prints the overall p-value from the model.

`resp_val()`

,`cv_error()`

and`pred_accuracy()`

did not work for formulas with transforming function for response terms, e.g.`log(response)`

.

- Fixed examples, to resolve issues with CRAN package checks.
- More model objects supported in
`p_value()`

.

`model_frame()`

to get the model frame from model objects, also of those models that don’t have a S3-generic model.frame-function.`var_names()`

to get cleaned variable names from model objects.`link_inverse()`

to get the inverse link function from model objects.

- The
`fun`

-argument in`typical_value()`

can now also be a named vector, to apply different functions for numeric and categorical variables.

- Fixed issue with specific model formulas in
`pred_vars()`

. - Fixed issue with specific model objects in
`resp_val()`

. - Fixed issue with nested models in
`re_var()`

.

`tidy_stan()`

to return a tidy summary of Stan-models.

`hdi()`

and`rope()`

now also work for`brmsfit`

-models, from package*brms*.`hdi()`

and`rope()`

now have a`type`

-argument, to return fixed, random or all effects for mixed effects models.

`typical_value()`

gets a “zero”-option for the`fun`

-argument.- Changes to
`icc()`

, which used`stats::sigma()`

and thus required R-version 3.3 or higher. Now should depend on R 3.2 again. `se()`

now also supports`stanreg`

and`stanfit`

objects.`hdi()`

now also supports`stanfit`

-objects.`std_beta()`

gets a`ci.lvl`

-argument, to specify the level of the calculated confidence interval for standardized coefficients.`get_model_pval()`

is now deprecated. Please use`p_value()`

instead.

`rope()`

to calculate the region of practical equivalence for MCMC samples.

- Added vignettes for various functions.
- Fixed issue with latest tidyr-update on CRAN.

`grpmean()`

to compute mean values by groups (One-way Anova).`hdi()`

to compute high density intervals (HDI) for MCMC samples.`find_beta()`

and`find_beta2()`

to find the shape parameters of a Beta distribution.`find_normal()`

and`find_cauchy()`

to find the parameters of a normal or cauchy distribution.