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.
$is_count = TRUE, when model is a count-model, and
$is_beta = TRUEfor models with beta-family.
pred_vars()checks that return value has only unique values.
zi-argument to return the variables from a model’s zero-inflation-formula.
dplyr::n(), to meet forthcoming changes in dplyr 0.8.0.
pca_rotate()now supports all rotations from
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).
icc()for non-Gaussian Bayes-models, a message is printed that recommends setting argument
resp_var()now also work for brms-models with additional response information (like
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.
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
re_grp_var()to find group factors of random effects in mixed models.
eta_sq()give more informative messages when using non-supported objects.
icc()give more informative warnings and messages.
tidy_stan()supports printing simplex parameters of monotonic effects of brms models.
encodingargument, 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).
grpmean()when variable name was passed as character vector.
r2()for glmmTMB models with
ar1random effects structure.
mediation()can now cope with models from different families, e.g. if the moderator or outcome is binary, while the treatment-effect is continuous.
clm2-objects from package ordinal.
anova_stats()gives a more informative message for non-supported models or ANOVA-options.
link_inverse()for models fitted with
grpmean()for grouped data frames, when grouping variable was an unlabelled factor.
model_frame()for coxph-models with polynomial or spline-terms.
mediation()for logical variables.
robust()was revised, getting more arguments to specify different types of covariance-matrix estimation, and handling these more flexible.
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
r2()gives more precise warnings for non-supported model-families.
weights-argument, to compute measures of association for contingency tables for weighted data.
"fisher"-option, to force Fisher’s Exact Test to be used.
icc()for generalized linear mixed models with Poisson or negative binomial families.
adjusted-argument, to calculate the adjusted and conditional ICC for mixed models.
weight.byis now deprecated and renamed into
grpmean()now also adjusts the
n-columm for weighted data.
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)).
equi_test()did not work for intercept-only models.
equi_test()etc. are now more generic, and function usage for each supported object is now included in the documentation.
print()-methods for some more functions, for a clearer output.
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.
stanmvreg-models are now supported by many functions.
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.
icc()now also computes the HDI for the ICC and random-effect variances. Use the
prob-argument to specify the limits of this interval.
model_family()now support clmm-models (package ordinal) and glmRob and lmRob-models (package robust).
multi.resp-argument, to return a list of family-informations for multivariate-response models (of class
multi.resp-argument, to return a list of link-inverse-functions for multivariate-response models (of class
p_value()now supports rlm-models (package MASS).
check_assumptions()for single models with
as.logical = FALSEnow has a nice print-method.
omega_sq()now also work for repeated-measure Anovas, i.e. Anova with error term (requires broom > 0.4.5).
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.
exponentiate = TRUEand
conf.int = FALSE.
reliab_test()returned an error when the provided data frame has less than three columns, instead of returning
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.
model_family()) now better support
vglm-models (package VGAM).
r2()now also calculates the standard error for brms or stanreg models.
loo-argument to calculate LOO-adjusted rsquared values for brms or stanreg models. This measure comes conceptionally closer to an adjusted r-squared measure.
eta_sq()etc.) are now also computed for mixed models.
n_eff()now computes the number of effective samples, and no longer its ratio in relation to the total number of samples.
tidy_stan()is now named neff_ratio, to avoid confusion.
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.
brmsfit-objects (esp. with random effects) more efficient.
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.
mwu()now should be a variable name from a variable in
x, and no longer a separate vector.
eta_sq()etc. when confidence intervals were computed with bootstrapping and the model-formula contained function calls like
p_value()for unconditional mixed models.
typical_value(), when argument
funfor factors was set to
tidy_stan()etc. for brmsfit-objects.
model_frame()with spline-terms when missing values were removed due to casewise deletion.
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
hdi()now accepts a vector of scalars to compute HDIs for multiple probability tresholds at once.
tidy_stan()was renamed into
prob, to be consistent with
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.
ci.lvl-argument to compute confidence intervals for the effect size statistics.
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
partial-argument to compute partial omega-squared.
anova.rms-objects from the rms-package.
model_frame()does not return duplicated column names.
tidy_stan()with incorrect n_eff statistics for sigma parameter in mixed models.
tidy_stan(), which did not work when
probswas of length greater than 2.
icc()with brmsfit-models, which was broken probably due to internal changes in brms.
tidy_stan()with more complex brmsfit-models.
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.
grpmean(), where values instead of value labels were printed if some categories were not present in the data.
contrasts()from package emmeans to compute p-values, which correclty indicate whether the sub-group mean is significantly different from the total mean.
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.
link_inverse()now support Zelig-relogit-models.
typical_value()gets an explicit
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
brmsfit-objects (models fitted with the brms-package).
fun = "weighted.mean",
typical_value()now checks if vector of weights is of same length as
grpmean()now also prints the overall p-value from the model.
typical_value()can now also be a named vector, to apply different functions for numeric and categorical variables.
tidy_stan()to return a tidy summary of Stan-models.
typical_value()gets a “zero”-option for the
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
hdi()now also supports
ci.lvl-argument, to specify the level of the calculated confidence interval for standardized coefficients.
get_model_pval()is now deprecated. Please use
rope()to calculate the region of practical equivalence for MCMC samples.