Changelog
Source:NEWS.md
ggeffects 1.1.4
Bug fixes
Fixed issue with wrong standard errors for predicting random effect groups for more multiple levels.
Fixed issue in
ggemmeans()
, which did not correctly averaged over character vectors when these were hold constant.Fixed bug for models of class
lme
whentype = "re"
was requested.
ggeffects 1.1.1
CRAN release: 20210729
ggeffects 1.1.0
CRAN release: 20210430
Breaking Changes
Prediction intervals (where possible, or when
type = "random"
), are now always based on sigma^2 (i.e.insight::get_sigma(model)^2
). This is in line withinterval = "prediction"
for lm, or for predictions based on simulations (whentype = "simulate"
).print()
now uses the name of the focal variable as column name (instead) of"x"
).
New function

collapse_by_group()
, to generate a data frame where the response value of the raw data is averaged over the levels of a (random effect) grouping factor.
General
A new vignette was added related to the definition and meaning of “marginal effects” and “adjusted predictions”. To be more strict and to avoid confusion with the term “marginal effect”, which meaning may vary across fields, either “marginal effects” was replaced by “adjusted predictions”, or “adjusted predictions” was added as term throughout the package’s documentation and vignettes.
Allow confidence intervals when predictions are conditioned on random effect groups (i.e. when
type = "random"
andterms
includes a random effect group factor).Predicted response values based on
simulate()
(i.e. whentype = "simulate"
) is now possible for more model classes (see?ggpredict
).ggpredict()
now computes confidence intervals for some edge cases where it previously failed (e.g. some models that do not compute standard errors for predictions, and where a factor was included in the model and not the focal term).plot()
gains acollapse.group
argument, which  in conjunction withadd.data
 averages (“collapses”) the raw data by the levels of the group factors (random effects).data_grid()
was added as more common alias fornew_data()
.
Bug fixes
ggpredict()
andplot()
for survivalmodels now always start with time = 1.Fixed issue in
print()
for survivalmodels.Fixed issue with
type = "simulate"
forglmmTMB
models.Fixed issue with
gamlss
models that hadrandom()
function in the model formula.Fixed issue with incorrect backtransformation of predictions for
geeglm
models.
ggeffects 1.0.2
CRAN release: 20210317
Breaking changes

residuals.type
argument inplot()
is deprecated. Always using"working"
residuals.
General
pretty_range()
andvalues_at()
can now also be used as function factories.plot()
gains alimit.range
argument, to limit the range of the prediction bands to the range of the data.
ggeffects 1.0.1
CRAN release: 20201214
General
 Fixed CRAN check issues.
 Added argument
interval
toggemmeans()
, to either compute confidence or prediction intervals.
ggeffects 1.0.0
CRAN release: 20201129
New functions

pool_predictions()
, to pool multipleggeffects
objects. This can be used when predicted values or estimated marginal means are calculated for models fit to multiple imputed datasets.
General
 The function
residualize_over_grid()
is now exported.  The backtransformation of the responsevariable (if these were log or square roottransformed in the model) now also works with square roottransformations and correctly handles
log1p()
andlog(mu + x)
.  Since standard errors were on the linkscale and not backtransformed for nonGaussian models, these are now no longer printed (to avoid confusion between standard errors on the linkscale and predictions and confidence intervals on the responsescale).
Bug fixes
 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 inggemmeans()
.  Fixed issue in
ggemmeans()
for models from nlme.  Fixed issue with
plot()
for some models inggeffect()
.  Fixed issue with computation of confidence intervals for zeroinflated models with offsetterm.
ggeffects 0.16.0
CRAN release: 20200913
Breaking changes
 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 logtransformed variables. Thus, exponentiation like using
terms = "predictor [exp]"
is no longer necessary.
General

plot()
now can also create partial residuals plots. There, argumentsresiduals
,residuals.type
andresiduals.line
were added to add partial residuals, the type of residuals and a possible loessfit regression line for the residual data.
Bug fixes
 The message for models with a backtransformation to the response scale (all nonGaussian models), that standard errors are still on the linkscale, did not show up for models of class
glm
since some time. Should be fixed now.  Fixed issue with
ggpredict()
andrlmerMods
models when using factors as adjusted terms.  Fixed issue with brmsmultiresponse models.
ggeffects 0.15.1
CRAN release: 20200727
Bug fixes
 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()
.
ggeffects 0.15.0
CRAN release: 20200616
Changes to functions

ggpredict()
gets a newtype
option,"zi.prob"
, to predict the zeroinflation probability (for models from pscl, glmmTMB and GLMMadaptive).  When model has logtransformed response variable and
add.data = TRUE
inplot()
, the raw data points are also transformed accordingly. 
plot()
withadd.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.
ggeffects 0.14.2
CRAN release: 20200314
General
 ggeffects now requires glmmTMB version 1.0.0 or higher.
 Added humanreadable aliasoptions to the
type
argument.
Bug fixes
 Fixed issue when logtransformed predictors where held constant and their typical value was negative.
 Fixed issue when plotting raw data to a plot with categorical predictor in the xaxis, which had numeric factor levels that did not start at
1
.  Fixed issues for model objects that used (log) transformed
offset()
terms.
ggeffects 0.14.0
CRAN release: 20191216
General
 Reduce package dependencies.

plot(rawdata = TRUE)
now also works for objects fromggemmeans()
. 
ggpredict()
now computes confidence intervals for predictions fromgeeglm
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 thecondition
argument to hold the number of trials constant at different values.  Improve
print()
.
Bug fixes
 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.
ggeffects 0.13.0
CRAN release: 20191108
New supported models

bracl
,brmultinom
(package brglm2) and models from packages bamlss and R2BayesX.
General
 Updated package dependencies.

plot()
now uses dodgeposition for raw data for categorical xaxis, to align raw data points with points and error bars geoms from predictions.  Updated and rearranged internal color palette, especially to have a better behaviour when selecting colors from continuous palettes (see
show_pals()
).
New functions
 Added a
vcov()
function to calculate variancecovariance matrix for marginal effects.
Changes to Functions

ggemmeans()
now also acceptstype = "re"
andtype = "re.zi"
, to add random effects variances to prediction intervals for mixed models.  The ellipsesargument
...
is now passed down to thepredict()
method for gamlssobjects, so predictions can be computed for sigma, nu and tau as well.
Bug fixes
 Fixed issue with wrong order of plot xaxis for
ggeffect()
, when one term was a character vector.
ggeffects 0.12.0
CRAN release: 20190903
Breaking Changes
 The use of
ggaverage()
is discouraged, and so it was removed.  The name
rprs_values()
is now deprecated, the function is namedvalues_at()
, and its alias isrepresentative_values()
.  The
x.as.factor
argument defaults toTRUE
.
General

ggpredict()
now supports cumulative link and ordinal vglm models from package VGAM.  More informative error message for clmmmodels when
terms
included random effects. 
add.data
is an alias for therawdata
argument inplot()
. 
ggpredict()
andggemmeans()
now also support predictions for gam models fromziplss
family.
ggeffects 0.11.0
CRAN release: 20190701
General
 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 websitevignettes, so links on website are no longer broken.

values_at()
is an alias forrprs_values()
.
Changes to functions

ggpredict()
now supports prediction intervals for models from MCMCglmm. 
ggpredict()
gets aback.transform
argument, to tranform predicted values from logtransformed responses back to their original scale (the default behaviour), or to allow predictions to remain on logscale (new). 
ggpredict()
andggemmeans()
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 fromplot()
now also applies to error bars for categorical variables on the xaxis.
ggeffects 0.10.0
CRAN release: 20190513
General
 Better support, including confidence intervals, for some of the already supported model types.
 New packagevignette Logistic Mixed Effects Model with Interaction Term.
New supported models

gamlss
,geeglm
(package geepack),lmrob
andglmrob
(package robustbase),ols
(package rms),rlmer
(package robustlmm),rq
andrqss
(package quantreg),tobit
(package AER),survreg
(package survival)
Changes to functions
 The steps for specifying a range of values (e.g.
terms = "predictor [1:10]"
) can now be changed withby
, 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
inggpredict()
) now also works for following modelobjects:coxph
,plm
,polr
(and probably alsolme
andgls
, not tested yet). 
ggpredict()
gets aninterval
argument, to compute prediction intervals instead of confidence intervals. 
plot.ggeffects()
now allows different horizontal and vertical jittering forrawdata
whenjitter
is a numeric vector of length two.
Bug fixes
 Models with
AsIs
conversion from division of two variables as dependent variable, e.g.I(amount/frequency)
, now should work. 
ggpredict()
failed forMixMod
objects whenci.lvl=NA
.