IOMW 2020 Spotlight Talk: How Fair is to be Fair? Revisiting Test Equating under the NEAT Design (Session 3/4) [Online]

Abstract
The nonequivalent groups with anchor test design (NEAT) is widely used in test equating. Under this design, two groups of examinees are administered different test forms with each test form containing a subset of common items. Because test takers from different groups are assigned only one test form, missing score data emerge by design rendering some of the score distributions unavailable. The partial observability of the score data formally leads to an identifiability problem which has not been recognized as such in the equating literature, and has been faced from different perspectives, all of them making different assumptions in order to estimate the unidentified score distributions. In this paper, we formally specify the statistical model underlying the NEAT design and unveil the lack of identifiability of the parameters of interest that compose the equating transformation. We use the theory of partial identification to offer alternatives to traditional practices used to point identify the score distributions when conducting equating under the NEAT design.

Date: 
Tuesday, November 10, 2020 - 2:00pm
Building: 
Online session
Room: 
Zoom