subscore.sx: Computing subscores using Haberman's method based on both...

In subscore: Computing Subscores in Classical Test Theory and Item Response Theory

Computing subscores using Haberman's method based on both observed total scores and observed subscores.

Description

This function estimate true subscores based on both observed total scores and observed subscores using the method introduced by Haberman (2008) <doi:10.3102/1076998607302636>.

Usage

subscore.sx(test.data)

Arguments

test.data

A list that contains item responses of all subtests and the entire test, which can be obtained using function 'data.prep'.

Value

summary	Summary of obtained subscores (e.g., mean, sd).
PRMSE	PRMSEs of obtained subscores (for Haberman's methods only).
subscore.original	Original observed subscores and total score.
subscore.sx	Subscores that are estimated based on both the observed total score and observed subscore.

References

Haberman, S. J. (2008). "When can subscores have value?." Journal of Educational and Behavioral Statistics, 33(2), 204-229. doi:10.3102/1076998607302636.

Examples

       test.data<-data.prep(scored.data,c(3,15,15,20),
                            c("Algebra","Geometry","Measurement", "Math"))
       
       subscore.sx(test.data) 
       subscore.s(test.data)$Correlation
       subscore.s(test.data)$Disattenuated.correlation
       subscore.sx(test.data)$summary
       subscore.sx(test.data)$PRMSE
       subscore.sx(test.data)$subscore.sx

subscore documentation built on May 24, 2022, 5:07 p.m.