predict.quint: Predictions for new data with a QUINT object

In quint: Qualitative Interaction Trees

Predictions for new data with a QUINT object

Description

Predicts for (new) subjects the treatment subgroups (P1, P2 or P3) based on a fitted quint object. The meaning of the subgroups are based on the two treatment categories used to fit the quint object.

Usage

## S3 method for class 'quint'
predict(object, newdata, type = "class", ...)

Arguments

object	an object of the class “quint”.
newdata	a data frame with data on new subjects for whom predictions should be made. The data frame should contain at least the variables used in the splits of the fitted tree. It is not necessary to include the treatment variable.
type	character string denoting the type of predicted object to be returned. The default is set to type="class": a vector with predicted treatment subgroup classes per subject is returned. If set to "matrix", a matrix is returned with the leaf and corresponding node of the tree to which a subject is assigned.
...	optional additional arguments.

Value

One of the following objects is returned depending on output type specified in the function:

If type="class": vector of predicted treatment classes for every individual in the data set. Returns NA for subjects with missing values on one or more of the splitting variables.

If type="matrix": a matrix with predicted locations of subjects within the fitted tree. The leaf numbers are in the first column and the corresponding node numbers in the second column. Returns NA for subjects with missing values on one or more of the splitting variables.

See Also

quint, prune.quint

Examples

data(bcrp)
formula1<- I(cesdt1-cesdt3)~cond | nationality+marital+wcht1+age+
  trext+comorbid+disopt1+uncomt1+negsoct1

set.seed(10)
control1<-quint.control(maxl=5,B=2)
quint1<-quint(formula1, data= subset(bcrp,cond<3),control=control1) #Grow a QUINT tree

prquint1<-prune(quint1) #Prune QUINT tree to optimal size

#Predict for the same data set the treatment classes for patients individually:
predquint1<-predict(prquint1, newdata=subset(bcrp,cond<3), type='class')
predquint1

quint documentation built on July 2, 2022, 1:07 a.m.