Document Type


Date of Degree

Summer 2019

Degree Name

PhD (Doctor of Philosophy)

Degree In

Psychological and Quantitative Foundations

First Advisor

Lee, Won-Chan

Second Advisor

Kolen, Michael J

First Committee Member

Brennan, Robert

Second Committee Member

Welch, Catherine

Third Committee Member

Aloe, Ariel M

Fourth Committee Member

Tan, Aixin


Equating is a statistical process that is used to adjust scores on test forms so that scores on the forms can be used interchangeably. This dissertation offered intensive investigation of beta true and observed score methods by comparing them to existing traditional and IRT equating methods under multiple designs and various conditions using real data, pseudo-test data and simulated data. Weighted and conditional bias, standard error of equating and root mean squared error were used to evaluate the accuracy of equating results obtained from the pseudo data and simulated data analyses. The single group equipercentile equating based on large sample sizes was used as the criterion equating. Overall, results showed that of the methods examined, the IRT methods performed best, followed by the chained equipercentile methods. Results from beta methods presented different trends from traditional and IRT methods for both the random group and common item nonequivalent groups designs. Beta true scores methods were less sensitive to group difference compared to traditional methods. The length of common items played an important role in the stability of results of beta true score methods.


Equating, True score


xx, 175 pages


Includes bibliographical references (pages 100-108).


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Copyright © 2019 Shichao Wang