summary.DIFtree: Summary for fitted Item focussed Trees

In DIFtree: Item Focussed Trees for the Identification of Items in Differential Item Functioning

Description

The function takes an object of class "DIFtree" and returns an useful summary with an overiew of all executed splits during the estimation procedure.

Usage

## S3 method for class 'DIFtree'
summary(object, ...)

## S3 method for class 'summary.DIFtree'
print(x, ...)

Arguments

object	Object of class DIFtree
...	Further arguments passed to or from other methods
x	Object of class summary.DIFtree

Value

Object of class "summary.DIFtree". An object of class "summary.DIFtree" is a list containing the following components:

stats	Useful overview of detected DIF items, responsible variables and executed splits
nosplits	Total number of executed splits during the estimation procedure

Author(s)

Moritz Berger <[e-mail]>
http://www.imbie.uni-bonn.de/personen/dr-moritz-berger/

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, predict.DIFtree

Examples

data(data_sim_Rasch)
 
Y <- data_sim_Rasch[,1]
X <- data_sim_Rasch[,-1]
 
## Not run: 
 
mod <- DIFtree(Y=Y,X=X,model="Logistic",type="udif",alpha=0.05,nperm=1000,trace=TRUE)
 
summary(mod)

## End(Not run)

DIFtree documentation built on July 8, 2020, 6:49 p.m.