predict.DIFtree function

Prediction from fitted Item focussed Trees

The function returns predictions of item parameters obtained by item focussed recursive partitioning in dichotomous or polytomous items.

## S3 method for class 'DIFtree'
predict(object, item, newdata, ...)

Arguments

• object: Object of class DIFtree
• item: Number of the item, for which the prediction shall be returned
• newdata: New data.frame, for which the prediction shall be returned
• ...: Further arguments passed to or from other methods

Details

For "Rasch" model the function returns the predicted item difficulty. For "Logistic" models the function returns the predicted intercept and/or slope. For "PCM" the function returns the predicted threshold parameters.

Examples

data(data_sim_Rasch)
 
Y <- data_sim_Rasch[,1]
X <- data_sim_Rasch[,-1]

Xnew <- data.frame("x1"=c(0,1),"x2"=c(-1.1,2.5),"x3"=c(1,0),"x4"=c(-0.2,0.7))
 
## Not run:

 
mod <- DIFtree(Y=Y,X=X,model="Logistic",type="udif",alpha=0.05,nperm=1000,trace=TRUE)
 
predict(mod,item=1,Xnew)
## End(Not run)

References

Berger, Moritz and Tutz, Gerhard (2016): Detection of Uniform and Non-Uniform Differential Item Functioning by Item Focussed Trees, Journal of Educational and Behavioral Statistics 41(6), 559-592.

Bollmann, Stella, Berger, Moritz & Tutz, Gerhard (2018): Item-Focussed Trees for the Detection of Differential Item Functioning in Partial Credit Models, Educational and Psychological Measurement 78(5), 781-804.

Tutz, Gerhard and Berger, Moritz (2016): Item focussed Trees for the Identification of Items in Differential Item Functioning, Psychometrika 81(3), 727-750.

See Also

DIFtree, plot.DIFtree, summary.DIFtree

Author(s)

Moritz Berger moritz.berger@imbie.uni-bonn.de

http://www.imbie.uni-bonn.de/personen/dr-moritz-berger/