mid.conditional {midr} | R Documentation |
Calculate ICE of MID Models
Description
mid.conditional()
creates an object to draw ICE curves of a MID model.
Usage
mid.conditional(
object,
variable,
data = NULL,
keep.effects = TRUE,
n.samples = 100L,
max.nrow = 100000L,
type = c("response", "link")
)
## S3 method for class 'mid.conditional'
print(x, digits = max(3L, getOption("digits") - 2L), ...)
Arguments
object |
a "mid" object. |
variable |
a character string or expression specifying the variable for the ICE calculation. |
data |
a data frame containing observations for which ICE values are calculated. If not passed, data is extracted from |
keep.effects |
logical. If |
n.samples |
integer. The number of sample points for the calculation. |
max.nrow |
an integer specifying the maximum number of rows of the output data frames. |
type |
the type of prediction required. The default is "response". "link" is possible if the MID model uses a link function. |
x |
a "mid.conditional" object to be printed. |
digits |
an integer specifying the minimum number of significant digits to be printed. |
... |
additional parameters to be passed to |
Details
mid.conditional()
obtains predictions for hypothetical observations from a MID model and returns a "mid.conditional" object.
The graphing functions ggmid()
and plot()
can be used to generate the ICE curve plots.
Value
mid.conditional()
returns an object of class "mid.conditional" with the following components:
terms |
the character vector of relevant terms. |
observed |
the data frame of the actual observations and the corresponding predictions. |
conditional |
the data frame of the hypothetical observations and the corresponding predictions. |
values |
the sample points of the variable. |
Examples
data(airquality, package = "datasets")
mid <- interpret(Ozone ~ .^2, airquality, lambda = 1)
mc <- mid.conditional(mid, "Wind", airquality)
mc