ggeffects 1.0.1.001 Unreleased

Breaking changes

  • residuals.type argument in plot() is deprecated. Always using "working" residuals.

General

  • 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.

Bug fixes

  • Fixed issue with unnecessary back-transformation of log-transformed offset-terms fro glmmTMB models.

ggeffects 1.0.1 2020-12-14

General

  • Fixed CRAN check issues.
  • Added argument interval to ggemmeans(), to either compute confidence or prediction intervals.

ggeffects 1.0.0 2020-11-29

New supported models

  • averaging (package MuMIn)

New functions

  • 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.

General

  • 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).

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 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.

ggeffects 0.16.0 2020-09-13

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 log-transformed variables. Thus, exponentiation like using terms = "predictor [exp]" is no longer necessary.

New supported models

  • mlogit (package mlogit)

General

  • 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.

Bug fixes

  • 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.

ggeffects 0.15.1 2020-07-27

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 2020-06-16

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 2020-04-20

General

  • Fixed issues to due changes in other CRAN packages.

ggeffects 0.14.2 2020-03-14

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 2020-01-28

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 2019-12-16

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 2019-11-08

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 2019-09-03

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 2019-07-01

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 2019-05-13

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.