Efficient Standard Errors in Item Response Theory Models for Short Tests
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| Title: | Efficient Standard Errors in Item Response Theory Models for Short Tests |
|---|---|
| Language: | English |
| Authors: | Ippel, Lianne (ORCID |
| Source: | Educational and Psychological Measurement. Jun 2020 80(3):461-475. |
| 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: http://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 15 |
| Publication Date: | 2020 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Item Response Theory, Error of Measurement, Accuracy, Standards, Guidelines, Models, Test Format, Item Analysis, Maximum Likelihood Statistics, Mathematical Formulas |
| DOI: | 10.1177/0013164419882072 |
| ISSN: | 0013-1644 |
| Abstract: | In dichotomous item response theory (IRT) framework, the asymptotic standard error (ASE) is the most common statistic to evaluate the precision of various ability estimators. Easy-to-use ASE formulas are readily available; however, the accuracy of some of these formulas was recently questioned and new ASE formulas were derived from a general asymptotic theory framework. Furthermore, exact standard errors were suggested to better evaluate the precision of ability estimators, especially with short tests for which the asymptotic framework is invalid. Unfortunately, the accuracy of exact standard errors was assessed so far only in a very limiting setting. The purpose of this article is to perform a global comparison of exact versus (classical and new formulations of) asymptotic standard errors, for a wide range of usual IRT ability estimators, IRT models, and with short tests. Results indicate that exact standard errors globally outperform the ASE versions in terms of reduced bias and root mean square error, while the new ASE formulas are also globally less biased than their classical counterparts. Further discussion about the usefulness and practical computation of exact standard errors are outlined. |
| Abstractor: | As Provided |
| Entry Date: | 2020 |
| Accession Number: | EJ1253240 |
| Database: | ERIC |
| Abstract: | In dichotomous item response theory (IRT) framework, the asymptotic standard error (ASE) is the most common statistic to evaluate the precision of various ability estimators. Easy-to-use ASE formulas are readily available; however, the accuracy of some of these formulas was recently questioned and new ASE formulas were derived from a general asymptotic theory framework. Furthermore, exact standard errors were suggested to better evaluate the precision of ability estimators, especially with short tests for which the asymptotic framework is invalid. Unfortunately, the accuracy of exact standard errors was assessed so far only in a very limiting setting. The purpose of this article is to perform a global comparison of exact versus (classical and new formulations of) asymptotic standard errors, for a wide range of usual IRT ability estimators, IRT models, and with short tests. Results indicate that exact standard errors globally outperform the ASE versions in terms of reduced bias and root mean square error, while the new ASE formulas are also globally less biased than their classical counterparts. Further discussion about the usefulness and practical computation of exact standard errors are outlined. |
|---|---|
| ISSN: | 0013-1644 |
| DOI: | 10.1177/0013164419882072 |
