ggeffects 0.15.1

New supported models

• mclogit (package mclogit)

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

Changes to functions

• 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.

Bug fixes

• Fix issues in cluster-robust variance-covariance estimation when vcov.type was not specified.

ggeffects 0.14.3

General

• Fixed issues to due changes in other CRAN packages.

ggeffects 0.14.2

General

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

Bug fixes

• 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.

ggeffects 0.14.1

General

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

New supported models

• mixor (package mixor), cgam, cgamm (package cgam)

Bug fixes

• Fix CRAN check issues due to latest emmeans update.

ggeffects 0.14.0

Breaking Changes

• The argument x.as.factor is considered as less useful and was removed.

New supported models

• fixest (package fixest), glmx (package glmx).

General

• 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().

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

Breaking Changes

• The use of emm() is discouraged, and so it was removed.

New supported models

• bracl, brmultinom (package brglm2) and models from packages bamlss and R2BayesX.

General

• 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()).

New functions

• Added a vcov() function to calculate variance-covariance matrix for marginal effects.

Changes to Functions

• 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.

Bug fixes

• Fixed issue with wrong order of plot x-axis for ggeffect(), when one term was a character vector.

ggeffects 0.12.0

Breaking Changes

• 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.

General

• 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.

Changes to Functions

• 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.

Bug fixes

• 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.

ggeffects 0.11.0

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 website-vignettes, so links on website are no longer broken.
• values_at() is an alias for rprs_values().

New supported models

• betabin, negbin (package aod), wbm (package panelr)

Changes to functions

• 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.

Bug fixes

• Fixed issue with glmmTMB models that included model weights.

ggeffects 0.10.0

General

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

New supported models

• 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)

Changes to functions

• 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.

Bug fixes

• 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.

ggeffects 0.9.0

General

• 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.

New supported models

• 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 functions

• 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.

Changes to functions

• 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.

Bug fixes

• 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.

ggeffects 0.8.0

General

• 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.

New supported models

• 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.

New functions

• 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().

Changes to functions

• 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().

Bug fixes

• 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.