brms (version 0.10.0)

marginal_effects.brmsfit: Display marginal effects of predictors

Description

Display marginal effects of one or more numeric and/or categorical predictors including interaction effects of order 2.

Usage

"marginal_effects"(x, effects = NULL, conditions = NULL, re_formula = NA, robust = FALSE, probs = c(0.025, 0.975), method = c("fitted", "predict"), ...)
marginal_effects(x, ...)
"plot"(x, ncol = NULL, points = FALSE, rug = FALSE, theme = ggplot2::theme(), ask = TRUE, do_plot = TRUE, ...)

Arguments

x

An object usually of class brmsfit

effects

An optional character vector naming effects (main effects or interactions) for which to compute marginal plots. If NULL (the default), plots for all effects are generated.

conditions

An optional data.frame containing variable values to marginalize on. Each effect defined in effects will be plotted separately for each row of data. The row names of data will be treated as titles of the subplots. It is recommended to only define a few rows in order to keep the plots clear. If NULL (the default), numeric variables will be marginalized by using their means and factors will get their reference level assigned.

re_formula

A formula containing random effects to be considered in the marginal predictions. If NULL, include all random effects; if NA (default), include no random effects.

robust

If FALSE (the default) the mean is used as the measure of central tendency. If TRUE the median is used instead.

probs

The quantiles to be used in the computation of credible intervals (defaults to 2.5 and 97.5 percent quantiles)

method

Either "fitted" or "predict". If "fitted", plot marginal predictions of the regression curve. If "predict", plot marginal predictions of the responses.

...

Currently ignored.

ncol

Number of plots to display per column for each effect. If NULL (default), ncol is computed internally based on the number of rows of data.

points

Logical; indicating whether the original data points should be added via geom_point. Default is FALSE. Note that only those data points will be added that match the specified conditions defined in conditions.

rug

Logical; indicating whether a rug representation of predictor values should be added via geom_rug. Default is FALSE.

theme

A theme object modifying the appearance of the plots. For some basic themes see ggtheme. Can be defined globally for the current session, via theme_set.

ask

logical; indicates if the user is prompted before a new page is plotted. Only used if do_plot is TRUE.

do_plot

logical; indicates if plots should be plotted directly in the active graphic device. Defaults to TRUE.

Value

An object of class brmsMarginalEffects, which is a named list with one element per effect containing all information required to generate marginal effects plots. The corresponding plot method returns a named list of ggplot objects, which can be further customized using the ggplot2 package.

Details

NA values within factors in conditions, are interpreted as if all dummy variables of this factor are zero. This allows, for instance, to make predictions of the grand mean when using sum coding.

Examples

## Not run: 
# fit <- brm(count ~ log_Age_c + log_Base4_c * Trt_c + (1 | patient),
#            data = epilepsy, family = poisson()) 
# ## plot all marginal effects
# plot(marginal_effects(fit), ask = FALSE)
# ## only plot the marginal interaction effect of 'log_Base4_c:Trt_c'
# ## for different values for 'log_Age_c'
# mdata <- data.frame(log_Age_c = c(-0.3, 0, 0.3))
# plot(marginal_effects(fit, effects = "log_Base4_c:Trt_c", 
#                       data = mdata))
# ## also incorporate random effects variance over patients
# ## and add a rug representation of predictor values
# plot(marginal_effects(fit, effects = "log_Base4_c:Trt_c", 
#                       data = mdata, re_formula = NULL), rug = TRUE)
# ## End(Not run)

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