Estimating Population Characteristics From Sparse Matrix Samples of Item Responses
Bibliographic Data
| ID | 23364950 |
|---|---|
| Authors | Robert J Mislevy (0000-0001-5016-0625, Boston College, corresponding author), Albert E Beaton (Boston College), Bruce Kaplan (0000-0003-3400-642X, Boston College), Kathleen M Sheehan (0000-0003-1497-1345, Boston College) |
| Year | 1992 |
| Volume | 29 |
| Issue | 2 |
| Pages | 133-161 |
| Publication date | 1992-06-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Educational Measurement (JOURNAL) |
| Journal identifiers | ISSN: 0022-0655 • E-ISSN: 1745-3984 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/j.1745-3984.1992.tb00371.x |
| OpenAlex | W1988703391 |
| Language | EN |
| Citations received | 73 |
| References cited | 17 |
The multiple‐matrix item sampling designs that provide information about population characteristics most efficiently administer too few responses to students to estimate their proficiencies individually. Marginal estimation procedures, which estimate population characteristics directly from item responses, must be employed to realize the benefits of such a sampling design. Numerical approximations of the appropriate marginal estimation procedures for a broad variety of analyses can be obtained by constructing, from the results of a comprehensive extensive marginal solution, files of plausible values of student proficiencies. This article develops the concepts behind plausible values in a simplified setting, sketches their use in the National Assessment of Educational Progress (NAEP), and illustrates the approach with data from the Scholastic Aptitude Test (SA T).
Aptitude · Econometrics · Estimation · Mathematics education · Matrix (chemical analysis) · Population · Sampling (signal processing) · Statistics · Test (biology) · Variety (cybernetics) · Computer Science · Demography · Engineering · Mathematics · Optimal Experimental Design Methods · Psychometric Methodologies and Testing · Statistical Methods and Bayesian Inference
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| Unique citing works | 73 |
|---|---|
| Citations per year | 2,21 |
| Citation span | 1993 - 2026 (34) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 70 |