Efficient Corrections for Standardized Person-Fit Statistics
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| Publicado en: | Psychometrika vol. 89, no. 2 (Jun 2024), p. 569 |
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| Autor principal: | |
| Otros Autores: | , |
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Springer Nature B.V.
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| Acceso en línea: | Citation/Abstract Full Text - PDF |
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| 024 | 7 | |a 10.1007/s11336-024-09960-x |2 doi | |
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| 045 | 2 | |b d20240601 |b d20240630 | |
| 084 | |a 69716 |2 nlm | ||
| 100 | 1 | |a Gorney, Kylie |u Michigan State University, Department of Counseling, Educational Psychology, and Special Education, East Lansing, USA (GRID:grid.17088.36) (ISNI:0000 0001 2195 6501) | |
| 245 | 1 | |a Efficient Corrections for Standardized Person-Fit Statistics | |
| 260 | |b Springer Nature B.V. |c Jun 2024 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Many popular person-fit statistics belong to the class of standardized person-fit statistics, T, and are assumed to have a standard normal null distribution. However, in practice, this assumption is incorrect since T is computed using (a) an estimated ability parameter and (b) a finite number of items. Snijders (Psychometrika 66(3):331–342, 2001) developed mean and variance corrections for T to account for the use of an estimated ability parameter. Bedrick (Psychometrika 62(2):191–199, 1997) and Molenaar and Hoijtink (Psychometrika 55(1):75–106, 1990) developed skewness corrections for T to account for the use of a finite number of items. In this paper, we combine these two lines of research and propose three new corrections for T that simultaneously account for the use of an estimated ability parameter and the use of a finite number of items. The new corrections are efficient in that they only require the analysis of the original data set and do not require the simulation or analysis of any additional data sets. We conducted a detailed simulation study and found that the new corrections are able to control the Type I error rate while also maintaining reasonable levels of power. A real data example is also included. | |
| 653 | |a Statistical analysis | ||
| 653 | |a Skewness | ||
| 653 | |a Simulation | ||
| 653 | |a Statistics | ||
| 653 | |a Datasets | ||
| 653 | |a Normal distribution | ||
| 700 | 1 | |a Sinharay, Sandip |u Educational Testing Service, Princeton, USA (GRID:grid.286674.9) (ISNI:0000 0004 1936 9051) | |
| 700 | 1 | |a Eckerly, Carol |u Educational Testing Service, Princeton, USA (GRID:grid.286674.9) (ISNI:0000 0004 1936 9051) | |
| 773 | 0 | |t Psychometrika |g vol. 89, no. 2 (Jun 2024), p. 569 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3066166501/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3066166501/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |