NEWS.md
null_model()
now also works for non-mixed models.get_variance()
now also computes variance components for models (from mixed models packages) without random effects.afex_aov
and aovlist
(i.e. Anova with error term).NULL
strings under R 4.0.0.get_variance()
for models from Gamma family.clean_names()
.find_formula.lme()
under R 4.0.0.clean_names()
under R-devel.null_model()
.)model_info()
, link_inverse()
and link_function()
for MCMCglmm.find_parameters()
and clean_parameters()
for brmsfit models with specific variable name patterns.format_ci()
when confidence interval only contained NA
s and width
was set to "auto"
.find_formula()
for mixed models when formula contained parentheses in the non-random parts, around a certain set of predictors.get_priors.BFBayesFactor()
for BFMetat
class.clean_parameters.BFBayesFactor()
when model contained interaction terms and these were assigned to the “extra” component.model_info()
now only returns TRUE
for $is_ordinal
, when model is an ordinal or cumulative link model. In past versions, $is_ordinal
was also TRUE
for multinomial models.find_weights()
for merMod
models.get_data()
for models with weights, when weights also contained missing data.get_data()
for mixed models with complex offset-terms.get_statistic()
for zeroinfl models with theta-coefficients.get_statistic()
for lmerModLmerTest models with.find_parameters()
for brmsfit models for rare situations where a specific pattern of variables names, when used as random effects, did not properly separate fixed from random effects in the return value.find_parameters()
and get_parameters()
for mixed models with large samples and many random effects, and only fixed effects where requested.model_info()
now returns $is_multinomial
for multinomial (but not ordinal or cumulative) link models.format_value()
gets an as_percent
argument to format values as percentages.get_data()
for clmm2-models.get_data()
for models that used the lspline()
-function.get_statistic()
for multinom models.get_priors()
for stanreg models with flat intercept priors.brglm
(brglm), cgam
, cgamm
(cgam), cpglm
, cpglmm
(cplm), feglm
(apaca), glmmadmb
(glmmADMB), glmx
(glmx), partial support for mcmc
(coda), mixor
(mixor), MANOVA
, RM
(MANOVA.RM).format_ci()
(re-implemented and slightly enhanced from parameters), to format confidence/credible intervals.find_parameters()
now also works for BFBayesFactor
objects.get_data()
for model data with weights.format_value()
automatically uses scientific notation for very large numbers (> 1e+5). Furthermore, the check for integer values was made more robust, to avoid warnings when checking very large numbers for integer type.find_parameters()
, get_parameters()
and clean_parameters()
for BFBayesFactor
-objects.get_priors()
now works for stanmvreg
objects.model_info()
.find_random_slopes()
for panelr-models with multiple random-effect parts.zerotrunc
models.brmsfit
models with correlated random effects.clean_names()
.find_formula()
for mixed models, when random effects are written before any fixed effects terms (like social ~ (1|school) + open + extro
).model_info()
for VGAM models, where logit-link was not always correctly identified.get_priors()
for brmsfit models, where parameters of conditional and zero-inflated model components had identical names. This caused errors in bayestestR::simulate_prior()
.get_parameters()
and get_priors()
now return column names according to our naming conventions (i.e. capitalized column names).model_info()
returned both $is_zeroinf
and $is_zero_inflated
for zero-inflated models. Now $is_zeroinf
is softly deprecated, so model_info()
will return $is_zero_inflated
only in future updates.aareg
(survival), brmultinom
and bracl
(brglm2), and wbgee
(panelr). Furthermore, for different model-types from panelr models (within-between, between, etc.) are now also supported.rma
models (metafor).get_statistic()
supports multinom
models (nnet).link_inverse()
gets a what
-argument, to return the link-inverse function for specific distribution parameters from gamls models.find_weights()
.get_statistic()
for glmmTMB models that won’t return any data.bayesx
(R2BayesX), bamlss
(bamlss) and flexsurvreg
(flexsurv). Note that support for these models is still somewhat experimental.get_data()
, get_parameters()
, find_parameters()
, clean_parameters()
, find_algorithm()
and get_priors()
(the two latter only for blavaan).get_statistic()
to return the test statistic of model estimates.get_varcov()
to return the variance-covariance matrix for models.supported_models()
to print a list of supported models.model_info()
now returns the element is_survival
for survival models.model_info()
now returns the element is_truncated
for truncated regression, or brmsfit models with trunc()
as additional response part.model_info()
now recognizes beta and beta inflated families from package gamlss.quantreg::nlrq()
).lme4::nlmer()
). Note that model-specification requires the random term to be written in parentheses, i.e. (slope | group)
.get_data()
, find_parameters()
and get_parameters()
for gamlss models.get_data()
for plm models, where the index
-argument was used in the plm()
-function call.get_data()
, find_predictors()
and find_variables()
for brmsfit multi-membership-models.is_model()
did not recognize objects of class anova
and manova
.model_info()
now correctly recognizes censored regression models from brmsfit.find_parameters()
and get_parameters()
with multinom models.clean_names()
for cases where variable transformations where made in specific patterns, like log(test/10)
.is_model()
function has been renamed to is_model_supported()
since it was unclear if the function checked the entered object was a model or a supported model in insight. The new is_model()
function checks if the entered object is a model object, while is_model_supported()
checks if a supported model object.find_statistic()
to return the test statistic of a regression model.format_value()
and format_table()
as utility-functions to format (model) output, especially for tabular output.color_if()
as utility-function to add color formatting to values, depending on certain conditions.find_parameters()
and get_parameters()
now also support objects of class sim
and sim.merMod
(from arm::sim()
).get_variance()
now also supports models of class clmm.find_predictors()
and find_variables()
now include the Euclidean distance matrix for spatial models from glmmTMB (returned as random effects element, or more precise, as random slope).find_formula()
now extracts group factors of random effects for gamlss models.find_parameters()
and get_parameters()
no longer show NA
coefficients from group factors of random effects for gamlss models.find_parameters()
and get_parameters()
did not work for multivariate response models of class brmsfit when argument parameters
was specified.get_data()
dropped value and variable label attributes, when model frame contained matrix variables (like splines).get_priors()
swapped column names location
and scale
for brmsfit -objects.get_parameters()
did not work for glmmTMB models without zero-inflation component.find_predictors()
did not remove parentheses from terms in multiple nested random effects.ziplss
or mvn
families.get_variance()
now supports models with Gamma-family.get_weights()
and find_weights()
now work for brms-models.