plot_predictions {marginaleffects} | R Documentation |
Plot predictions on the y-axis against values of one or more predictors (x-axis, colors/shapes, and facets).
The by
argument is used to plot marginal predictions, that is, predictions made on the original data, but averaged by subgroups. This is analogous to using the by
argument in the predictions()
function.
The condition
argument is used to plot conditional predictions, that is, predictions made on a user-specified grid. This is analogous to using the newdata
argument and datagrid()
function in a predictions()
call. Unspecified variables are held at their mean or mode.
See the "Plots" vignette and website for tutorials and information on how to customize plots:
https://vincentarelbundock.github.io/marginaleffects/articles/plot.html
https://vincentarelbundock.github.io/marginaleffects
plot_predictions(
model,
condition = NULL,
by = NULL,
type = NULL,
vcov = NULL,
conf_level = 0.95,
transform_post = NULL,
points = 0,
rug = FALSE,
gray = FALSE,
draw = TRUE,
...
)
model |
Model object |
condition |
Conditional predictions
|
by |
Marginal predictions
|
type |
string indicates the type (scale) of the predictions used to
compute contrasts or slopes. This can differ based on the model
type, but will typically be a string such as: "response", "link", "probs",
or "zero". When an unsupported string is entered, the model-specific list of
acceptable values is returned in an error message. When |
vcov |
Type of uncertainty estimates to report (e.g., for robust standard errors). Acceptable values:
|
conf_level |
numeric value between 0 and 1. Confidence level to use to build a confidence interval. |
transform_post |
A function applied to unit-level adjusted predictions and confidence intervals just before the function returns results. For bayesian models, this function is applied to individual draws from the posterior distribution, before computing summaries. |
points |
Number between 0 and 1 which controls the transparency of raw data points. 0 (default) does not display any points. |
rug |
TRUE displays tick marks on the axes to mark the distribution of raw data. |
gray |
FALSE grayscale or color plot |
draw |
|
... |
Additional arguments are passed to the |
A ggplot2
object or data frame (if draw=FALSE
)
mod <- lm(mpg ~ hp + wt, data = mtcars)
plot_predictions(mod, condition = "wt")
mod <- lm(mpg ~ hp * wt * am, data = mtcars)
plot_predictions(mod, condition = c("hp", "wt"))
plot_predictions(mod, condition = list("hp", wt = "threenum"))
plot_predictions(mod, condition = list("hp", wt = range))