Comparison of Methods for Adjusting Incorrect Assignments of Items to Subtests
Oblique Multiple Group Method Versus Confirmatory Common Factor Method
Bibliographic Data
| ID | 20286302 |
|---|---|
| Authors | Ilse Stuive (University of Groningen, corresponding author), Henk A L Kiers (0000-0002-4995-9349, University of Groningen), Marieke E Timmerman (0000-0003-1579-6964, University of Groningen) |
| Year | 2009 |
| Volume | 69 |
| Issue | 6 |
| Pages | 948-965 |
| Publication date | 2009-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Educational and Psychological Measurement (JOURNAL) |
| Journal identifiers | ISSN: 0013-1644 • E-ISSN: 1552-3888 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/0013164409332226 |
| OpenAlex | W2105488237 |
| Language | EN |
| Citations received | 5 |
| References cited | 19 |
A common question in test evaluation is whether an a priori assignment of items to subtests is supported by empirical data. If the analysis results indicate the assignment of items to subtests under study is not supported by data, the assignment is often adjusted. In this study the authors compare two methods on the quality of their suggestions to adjust incorrect assignments of items to subtests. The confirmatory common factor (CCF) method is often used in practice. However, previous research reported rather poor quality of the suggested adjustments. Therefore, the CCF method is compared with a less often used but promising method, the oblique multiple group (OMG) method. The authors compared both methods with a simulation study taken under various conditions. For each method, several adjustment procedures were studied. The best adjustment procedure within the OMG method performed better than or highly comparable to the procedures within the CCF method
A priori and a posteriori · Data mining · Quality (philosophy) · Statistics · Test (biology) · Advanced Statistical Modeling Techniques · Computer Science · Mathematics · Optimal Experimental Design Methods · Psychology · Psychometric Methodologies and Testing
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| Citations per year | 0.33 |
|---|---|
| Citation span | 2011 - 2021 (11) |
| Highly cited | No |