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The Missing Data Assumptions of the Nonequivalent Groups With Anchor Test (NEAT) Design and Their Implications for Test Equating CE NEAT

Author(s):
Sinharay, Sandip; Holland, Paul W.
Publication Year:
2009
Report Number:
RR-09-16
Source:
ETS Research Report
Document Type:
Report
Page Count:
53
Subject/Key Words:
Chain Equating (CE), Poststratification Equating (PE), IRT Observed-Score Equating, Item Response Theory (IRT), Frequency Estimation, Raking, Continuization, Non-Equivalent-Groups Anchor Test (NEAT) Design, Missing Data

Abstract

For each data set, we examine how the 3 equating methods perform when the missing data satisfy the assumptions made by only 1 of these equating methods. The chain equating method is somewhat more satisfactory overall than the other methods in out fair comparison of the methods; hence, we recommend that equating practitioners seriously consider the chain equating method when using the NEAT design. In addition, we conclude that the results from the different equating methods will tend to agree with each other when proper equating conditions are in place. Moreover, to uncover problems that might not reveal themselves otherwise, it is important for operational testing programs to apply multiple equating methods and study the differences among the results.

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