`residuals.type`

argument in`plot()`

is deprecated. Always using`"working"`

residuals.

`pretty_range()`

and`values_at()`

can now also be used as function factories.`plot()`

gains a`limit.range`

argument, to limit the range of the prediction bands to the range of the data.

Fixed issue with unnecessary back-transformation of log-transformed offset-terms fro

*glmmTMB*models.Fixed issues with plotting raw data when predictor on x-axis was a character vector.

Fixed issues from CRAN checks.

- Fixed CRAN check issues.
- Added argument
`interval`

to`ggemmeans()`

, to either compute confidence or prediction intervals.

`averaging`

(package**MuMIn**)

`pool_predictions()`

, to pool multiple`ggeffects`

objects. This can be used when predicted values or estimated marginal means are calculated for models fit to multiple imputed datasets.

- The function
`residualize_over_grid()`

is now exported. - The back-transformation of the response-variable (if these were log- or square root-transformed in the model) now also works with square root-transformations and correctly handles
`log1p()`

and`log(mu + x)`

. - Since standard errors were on the link-scale and not back-transformed for non-Gaussian models, these are now no longer printed (to avoid confusion between standard errors on the link-scale and predictions and confidence intervals on the response-scale).

- Fixed issue for mixed models when predictions should be conditioned on random effects variances (e.g.
`type = "random"`

or`"zi_random"`

), but random effects variances could not be calculated or were almost zero. - Fixed issue with confidence intervals for
`multinom`

models in`ggemmeans()`

. - Fixed issue in
`ggemmeans()`

for models from*nlme*. - Fixed issue with
`plot()`

for some models in`ggeffect()`

. - Fixed issue with computation of confidence intervals for zero-inflated models with offset-term.

- Package
*insight*since version 0.9.5 now returns the “raw” (untransformed, i.e. original) data that was used to fit the model also for log-transformed variables. Thus, exponentiation like using`terms = "predictor [exp]"`

is no longer necessary.

`mlogit`

(package**mlogit**)

`plot()`

now can also create partial residuals plots. There, arguments`residuals`

,`residuals.type`

and`residuals.line`

were added to add partial residuals, the type of residuals and a possible loess-fit regression line for the residual data.

- The message for models with a back-transformation to the response scale (all non-Gaussian models), that standard errors are still on the link-scale, did not show up for models of class
`glm`

since some time. Should be fixed now. - Fixed issue with
`ggpredict()`

and`rlmerMods`

models when using factors as adjusted terms. - Fixed issue with brms-multi-response models.

`mclogit`

(package**mclogit**)

- Fixed issues due to latest
*rstanarm*update. - Fixed some issues around categorical/cumulative
*brms*models when the outcome is numeric. - Fixed bug with factor level ordering when plotting raw data from
`ggeffect()`

.

`ggpredict()`

gets a new`type`

-option,`"zi.prob"`

, to predict the zero-inflation probability (for models from*pscl*,*glmmTMB*and*GLMMadaptive*).- When model has log-transformed response variable and
`add.data = TRUE`

in`plot()`

, the raw data points are also transformed accordingly. `plot()`

with`add.data = TRUE`

first adds the layer with raw data, then the points / lines for the marginal effects, so raw data points to not overlay the predicted values.- The
`terms`

-argument now also accepts the name of a variable to define specific values. See vignette*Marginal Effects at Specific Values*.

- Fix issues in cluster-robust variance-covariance estimation when
`vcov.type`

was not specified.

- Fixed issues to due changes in other CRAN packages.

*ggeffects*now requires*glmmTMB*version 1.0.0 or higher.- Added human-readable alias-options to the
`type`

-argument.

- Fixed issue when log-transformed predictors where held constant and their typical value was negative.
- Fixed issue when plotting raw data to a plot with categorical predictor in the x-axis, which had numeric factor levels that did not start at
`1`

. - Fixed issues for model objects that used (log) transformed
`offset()`

terms.

- Reduce package dependencies.
- New package-vignette
*(Cluster) Robust Standard Errors*.

`mixor`

(package**mixor**),`cgam`

,`cgamm`

(package**cgam**)

- Fix CRAN check issues due to latest
*emmeans*update.

- The argument
`x.as.factor`

is considered as less useful and was removed.

`fixest`

(package**fixest**),`glmx`

(package**glmx**).

- Reduce package dependencies.
`plot(rawdata = TRUE)`

now also works for objects from`ggemmeans()`

.`ggpredict()`

now computes confidence intervals for predictions from`geeglm`

models.- For
*brmsfit*models with`trials()`

as response variable,`ggpredict()`

used to choose the median value of trials were the response was hold constant. Now, you can use the`condition`

-argument to hold the number of trials constant at different values. - Improve
`print()`

.

- Fixed issue with
`clmm`

-models, when group factor in random effects was numeric. - Raw data is no longer omitted in plots when grouping variable is continuous and added raw data doesn’t numerically match the grouping levels (e.g., mean +/- one standard deviation).
- Fix CRAN check issues due to latest
*geepack*update.

- The use of
`emm()`

is discouraged, and so it was removed.

`bracl`

,`brmultinom`

(package**brglm2**) and models from packages**bamlss**and**R2BayesX**.

- Updated package dependencies.
`plot()`

now uses dodge-position for raw data for categorical x-axis, to align raw data points with points and error bars geoms from predictions.- Updated and re-arranged internal color palette, especially to have a better behaviour when selecting colors from continuous palettes (see
`show_pals()`

).

- Added a
`vcov()`

function to calculate variance-covariance matrix for marginal effects.

`ggemmeans()`

now also accepts`type = "re"`

and`type = "re.zi"`

, to add random effects variances to prediction intervals for mixed models.- The ellipses-argument
`...`

is now passed down to the`predict()`

-method for*gamlss*-objects, so predictions can be computed for sigma, nu and tau as well.

- Fixed issue with wrong order of plot x-axis for
`ggeffect()`

, when one term was a character vector.

- The use of
`ggaverage()`

is discouraged, and so it was removed. - The name
`rprs_values()`

is now deprecated, the function is named`values_at()`

, and its alias is`representative_values()`

. - The
`x.as.factor`

-argument defaults to`TRUE`

.

`ggpredict()`

now supports cumulative link and ordinal*vglm*models from package**VGAM**.- More informative error message for
*clmm*-models when`terms`

included random effects. `add.data`

is an alias for the`rawdata`

-argument in`plot()`

.`ggpredict()`

and`ggemmeans()`

now also support predictions for*gam*models from`ziplss`

family.

- Improved
`print()`

-method for ordinal or cumulative link models. - The
`plot()`

-method no longer changes the order of factor levels for groups and facets. `pretty_data()`

gets a`length()`

argument to define the length of intervals to be returned.

- Added “population level” to output from print-method for
*lme*objects. - Fixed issue with correct identification of gamm/gamm4 models.
- Fixed issue with weighted regression models from
*brms*. - Fixed broken tests due to changes of forthcoming
*effects*update.

- Revised docs and vignettes - the use of the term
*average marginal effects*was replaced by a less misleading wording, since the functions of**ggeffects**calculate marginal effects at the mean or at representative values, but not average marginal effects. - Replace references to internal vignettes in docstrings to website-vignettes, so links on website are no longer broken.
`values_at()`

is an alias for`rprs_values()`

.

`betabin`

,`negbin`

(package**aod**),`wbm`

(package*panelr*)

`ggpredict()`

now supports prediction intervals for models from*MCMCglmm*.`ggpredict()`

gets a`back.transform`

-argument, to tranform predicted values from log-transformed responses back to their original scale (the default behaviour), or to allow predictions to remain on log-scale (new).`ggpredict()`

and`ggemmeans()`

now can calculate marginal effects for specific values from up to three terms (i.e.`terms`

can be of lenght four now).- The
`ci.style`

-argument from`plot()`

now also applies to error bars for categorical variables on the x-axis.

- Fixed issue with
*glmmTMB*models that included model weights.

- Better support, including confidence intervals, for some of the already supported model types.
- New package-vignette
*Logistic Mixed Effects Model with Interaction Term*.

`gamlss`

,`geeglm`

(package**geepack**),`lmrob`

and`glmrob`

(package**robustbase**),`ols`

(package**rms**),`rlmer`

(package**robustlmm**),`rq`

and`rqss`

(package**quantreg**),`tobit`

(package**AER**),`survreg`

(package**survival**)

- The steps for specifying a range of values (e.g.
`terms = "predictor [1:10]"`

) can now be changed with`by`

, e.g.`terms = "predictor [1:10 by=.5]"`

(see also vignette*Marginal Effects at Specific Values*). - Robust standard errors for predictions (see argument
`vcov.fun`

in`ggpredict()`

) now also works for following model-objects:`coxph`

,`plm`

,`polr`

(and probably also`lme`

and`gls`

, not tested yet). `ggpredict()`

gets an`interval`

-argument, to compute prediction intervals instead of confidence intervals.`plot.ggeffects()`

now allows different horizontal and vertical jittering for`rawdata`

when`jitter`

is a numeric vector of length two.

- Models with
`AsIs`

-conversion from division of two variables as dependent variable, e.g.`I(amount/frequency)`

, now should work. `ggpredict()`

failed for`MixMod`

-objects when`ci.lvl=NA`

.