predict.repolr {repolr} | R Documentation |
Calculates predictions and standard errors of predictions for a fitted repolr
model object.
## S3 method for class 'repolr'
predict(object, newdata = NULL, se.fit = FALSE,
robust.var = TRUE, type = c("link", "response", "terms"), ...)
object |
is a model fitted using |
newdata |
optionally, a data frame in which to find variables with which to predict; if missing the model fitted values are reported. |
se.fit |
Logical indicating if standard errors are required. |
robust.var |
logical; if |
type |
is the type of prediction required. The default “ |
... |
further arguments passed to or from other methods. |
If newdata is missing predictions are based on the data used to fit the repolr
model. If newdata are supplied then the format of these data must conform to the same format required for model fitting using repolr
. See repolr
for details.
fit |
Predictions. |
se.fit |
Estimated standard errors. |
data(HHSpain)
mod.0 <- repolr(HHSpain~Sex*Time, data=HHSpain, categories=4, subjects="Patient",
times=c(1,2,5), corr.mod="uniform", alpha=0.5)
predict(mod.0, newdata = data.frame(Patient = rep(100, 3), Time = c(1, 2, 5),
Sex = factor(rep(1, 3), levels=1:2, labels=c("F", "M"))),
type="link", se.fit = TRUE)