- 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`

.

- Minor revisions to docs and vignettes.
- Reduce package dependencies.
- Better support, including confidence intervals, for some of the already supported model types.
- New package-vignette
*Customize Plot Appearance*.

`ggemmeans()`

now supports`type = "fe.zi"`

for**glmmTMB**-models, i.e. predicted values are conditioned on the fixed effects and the zero-inflation components of glmmTMB-models.`ggpredict()`

now supports**MCMCglmm**,**ivreg**and**MixMod**(package**GLMMadaptive**) models.`ggemmeans()`

now supports**MCMCglmm**and**MixMod**(package**GLMMadaptive**) models.`ggpredict()`

now computes confidence intervals for**gam**models (package**gam**).

`new_data()`

, to create a data frame from all combinations of predictor values. This data frame typically can be used for the`newdata`

-argument in`predict()`

, in case it is necessary to quickly create an own data frame for this argument.

`ggpredict()`

no longer stops when predicted values with confidence intervals for**glmmTMB**- and other zero-inflated models can’t be computed with`type = "fe.zi"`

, and only returns the predicted values without confidence intervals.- When
`ggpredict()`

fails to compute confidence intervals, a more informative error message is given. `plot()`

gets a`connect.lines`

-argument, to connect dots from plots with discrete x-axis.

`ggpredict()`

did not work with**glmmTMB**- and other zero-inflated models, when`type = "fe.zi"`

and model- or zero-inflation formula had a polynomial term that was held constant (i.e. not part of the`terms`

-argument).- Confidence intervals for zero-inflated models and
`type = "fe.zi"`

could not be computed when the model contained polynomial terms and a*very*long formula (issue with`deparse()`

, cutting off very long formulas). - The
`plot()`

-method put different spacing between groups when a numeric factor was used along the x-axis, where the factor levels where non equal-spaced. - Minor fixes regarding calculation of predictions from some already supported models
- Fixed issues with multiple response models of class
`lm`

in`ggeffects()`

. - Fixed issues with encoding in help-files.

- Minor changes to meet forthcoming changes in purrr.
- For consistency reasons, both
`type = "fe"`

and`type = "re"`

return population-level predictions for mixed effects models (**lme4**,**glmmTMB**). The difference is that`type = "re"`

also takes the random effect variances for prediction intervals into account. Predicted values at specific levels of random effect terms is described in the package-vignettes*Marginal Effects for Random Effects Models*and*Marginal Effects at Specific Values*. - Revised docs and vignettes.
- Give more informative warning for misspelled variable names in
`terms`

-argument. - Added custom (pre-defined) color-palettes, that can be used with
`plot()`

. Use`show_pals()`

to show all available palettes. - Use more appropriate calculation for confidence intervals of predictions for model with zero-inflation component.

`ggpredict()`

and`ggeffect()`

now support**brms**-models with additional response information (like`trial()`

).`ggpredict()`

now supports**Gam**,**glmmPQL**,**clmm**, and**zerotrunc**-models.- All models supported by the
**emmeans**should also work with the new`ggemmeans()`

-function. Since this function is quite new, there still might be some bugs, though.

`ggemmeans()`

to compute marginal effects by calling`emmeans::emmeans()`

.`theme_ggeffects()`

, which can be used with`ggplot2::theme_set()`

to set the**ggeffects**-theme as default plotting theme. This makes it easier to add further theme-modifications like`sjPlot::legend_style()`

or`sjPlot::font_size()`

.

- Added prediction-type based on simulations (
`type = "sim"`

) to`ggpredict()`

, currently for models of class**glmmTMB**and**merMod**. `x.cat`

is a new alias for the argument`x.as.factor`

.- The
`plot()`

-method gets a`ci.style`

-argument, to define different styles for the confidence bands for numeric x-axis-terms. - The
`print()`

-method gets a`x.lab`

-argument to print value labels instead of numeric values if`x`

is categorical. `emm()`

now also supports all prediction-types, like`ggpredict()`

.

- Fixed issue where confidence intervals could not be computed for variables with very small values, that differ only after the second decimal part.
- Fixed issue with
`ggeffect()`

, which did not work if data had variables with more that 8 digits (fractional part longer than 8 numbers). - Fixed issue with multivariate response models fitted with
**brms**or**rstanarm**when argument`ppd = TRUE`

. - Fixed issue with glmmTMB-models for
`type = "fe.zi"`

, which could mess up the correct order of predicted values for`x`

. - Fixed minor issue with glmmTMB-models for
`type = "fe.zi"`

or`type = "re.zi"`

, when first terms had the`[all]`

-tag. - Fixed minor issue in the
`print()`

-method for mixed effects models, when predictions were conditioned on all model terms and adjustment was only done for random effects (output-line “adjusted for”). - Fixed issue for mixed models, where confidence intervals were not completely calculated, if
`terms`

included a factor and`contrasts`

were set to other values than`contr.treatment`

. - Fixed issue with messed up order of confidence intervals for
`glm`

-object and heteroskedasticity-consistent covariance matrix estimation. - Fixed issue for
**glmmTMB**-models, when variables in dispersion or zero-inflation formula did not appear in the fixed effects formula. - The
`condition`

-argument was not always considered for some model types when calculating confidence intervals for predicted values.

- Support for monotonic predictors in
**brms**models (`mo()`

). - For generalized additive models, values for splines are no longer automatically prettified (which ensures smooth plots, without the need to use the
`[all]`

tag, i.e.`terms="... [all]"`

). - If splines or plolynomial terms are used, a message is printed to indicate that using the
`[all]`

tag, i.e.`terms="... [all]"`

, will produce smoother plots. - The package-vignette
*Marginal Effects at Specific Values*now has examples on how to get marginal effects for each group level of random effects in mixed models. - Revised
`print()`

-method, that - for larger data frames - only prints representative data rows. Use the`n`

-argument inside the`print()`

-method to force a specific number of rows to be printed.

- Added an
`n`

-tag for the`terms`

-argument in`ggpredict()`

and`ggeffect()`

, to give more flexibility according to how many values are used for “prettifying” large value ranges. - Added a
`sample`

-tag for the`terms`

-argument in`ggpredict()`

and`ggeffect()`

, to pick a random sample of values for plotting. `ggpredict()`

and`ggeffect()`

now also return the standard error of predictions, if available.- The
`jitter`

-argument in`plot()`

now also changes the amount of noise for plots of models with binary outcome (when`rawdata = TRUE`

).

- Fix issue with proper calculation of random effect variances for
**glmmTMB**models for`type="re"`

and`type="re.zi"`

in general, and also for models with`ar1`

random effects structure.

- Reduce package dependencies.
- Moved package
**effects**from dependencies to suggested packages, due to the restrictive requirements (R >= 3.5). - New
`print()`

-method, with a nicer print of the returned data frame. This method replaces the`summary()`

-method, which was removed. `ggeffect()`

now supports`clm2`

-models from the**ordinal**-package.`ggpredict()`

has improved support for`coxph`

-models from the**survival**-package (survival probabilities, cumulative hazards).

- The
`type`

-argument in`ggpredict()`

now has additional options,`type = "fe.zi"`

and`type = "re.zi"`

, to explicitely condition zero-inflated (mixed) models on their zero-inflation component. - The
`type`

-argument in`ggpredict()`

now has additional options,`type = "surv"`

and`type = "cumhaz"`

, to plot probabilities of survival or cumulative hazards from`coxph`

-models. `ggpredict()`

gets arguments`vcov.fun`

,`vcov.type`

and`vcov.args`

to calculate robust standard errors for confidence intervals of predicted values. These are based on the various`sandwich::vcov*()`

-functions, hence robust standard errors can be calculated for all models that are supported by`sandwich::vcov*()`

.- The
`plot()`

-method gets two arguments`line.size`

and`dot.size`

, to determine the size of the geoms. - The
`ci`

-argument for the`plot()`

-method now also accepts the character values`"dash"`

and`"dot"`

to plot dashed or dotted lines as confidence bands. - The
`terms`

-argument in`ggpredict()`

and`ggeffect()`

may also be a formula, which is more convenient for typing, but less flexible than specifying the terms as character vector with specific options.

- Fixed improper calculation of confidence intervals for hurdle- and zero-inflated models (from package
**pscl**), which could exceed the range of plausible values (e.g. below zero for incidence rates). - Fixed issues with calculation of confidence intervals for mixed models with polynomial terms.

- New vignette
*Different Output between Stata and ggeffects*.

`ggpredict()`

now automatically back-transforms predictions to the response scale for model with log-transformed response.`ggeffect()`

and`ggpredict()`

now automatically set numeric vectors with 10 or more unique values to representative values (see`rprs_values()`

), if these are used as second or third value in the`terms`

-argument (to represent a grouping structure).- Fix memory allocation issue in
`ggeffect()`

. `rprs_values()`

is now exported.- The
`pretty`

-argument is deprecated, because prettifying values almost always makes sense - so this is done automatically. `ggpredict()`

now supports`brmsfit`

-objects with categorical-family.`ggalleffect()`

has been removed.`ggeffect()`

now plots effects for all model terms if`terms = NULL`

.`gginteraction()`

and`ggpoly()`

have been removed, as`ggpredict()`

and`ggeffect()`

are more efficient and generic for plotting interaction or polynomial terms.

- Fix issues with categorical or ordinal outcome models (
`polr`

,`clm`

,`multinom`

) for`ggeffect()`

. - Fix issues with confidence intervals for mixed models with log-transformed response value.
- Fix issues with confidence intervals for generalized mixed models when response value was a rate or proportion created with
`cbind()`

in model formula.