Estimation of Conditional Standard Errors of Measurement for MLE Scores in MST

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Bibliographic Details
Title: Estimation of Conditional Standard Errors of Measurement for MLE Scores in MST
Language: English
Authors: Yuanyuan J. Stirn (ORCID 0009-0004-0115-1182), Won-Chan Lee (ORCID 0000-0002-5319-668X)
Source: Educational and Psychological Measurement. 2026 86(5):932-947.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 16
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Descriptors: Error of Measurement, Scores, Testing, Adaptive Testing, Maximum Likelihood Statistics, Test Length, Test Construction, Test Items, Simulation
DOI: 10.1177/00131644261420391
ISSN: 0013-1644
1552-3888
Abstract: This paper proposes an information-based analytic method for calculating the conditional standard error of measurement (CSEM) in multistage testing (MST) using maximum likelihood estimation. The accuracy of the proposed method was evaluated by comparing CSEMs computed using the analytic method with those obtained from simulation across the same four MST designs. The results show that analytic and simulation-based CSEMs converge as test length increases, indicating that the proposed method provides a reliable approximation for longer tests. However, shorter tests and more complex MST designs require additional items to achieve comparable accuracy. The study also compared the proposed method with Park et al.'s analytic approach. Practical implications of the proposed method are discussed.
Abstractor: As Provided
Entry Date: 20260101
Accession Number: EJ1517720
Database: ERIC
Description
Abstract:This paper proposes an information-based analytic method for calculating the conditional standard error of measurement (CSEM) in multistage testing (MST) using maximum likelihood estimation. The accuracy of the proposed method was evaluated by comparing CSEMs computed using the analytic method with those obtained from simulation across the same four MST designs. The results show that analytic and simulation-based CSEMs converge as test length increases, indicating that the proposed method provides a reliable approximation for longer tests. However, shorter tests and more complex MST designs require additional items to achieve comparable accuracy. The study also compared the proposed method with Park et al.'s analytic approach. Practical implications of the proposed method are discussed.
ISSN:0013-1644
1552-3888
DOI:10.1177/00131644261420391