Why Generalizability Theory Yields Better Results than Classical Test Theory [electronic resource] / Sandra H. Eason.
Generalizability theory provides a technique for accurately estimating the reliability of measurements. The power of this theory is based on the simultaneous analysis of multiple sources of error variances. Equally important, generalizability theory considers relationships among the sources of measu...
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Full Text (via ERIC) |
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| Main Author: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
[S.l.] :
Distributed by ERIC Clearinghouse,
1989.
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| Subjects: |
MARC
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| 100 | 1 | |a Eason, Sandra H. | |
| 245 | 1 | 0 | |a Why Generalizability Theory Yields Better Results than Classical Test Theory |h [electronic resource] / |c Sandra H. Eason. |
| 260 | |a [S.l.] : |b Distributed by ERIC Clearinghouse, |c 1989. | ||
| 300 | |a 34 p. | ||
| 500 | |a ERIC Document Number: ED314434. | ||
| 500 | |a ERIC Note: Paper presented at the Annual Meeting of the Mid-South Educational Research Association (Little Rock, AR, November 8-10, 1989). |5 ericd. | ||
| 520 | |a Generalizability theory provides a technique for accurately estimating the reliability of measurements. The power of this theory is based on the simultaneous analysis of multiple sources of error variances. Equally important, generalizability theory considers relationships among the sources of measurement error. Just as multivariate inferential statistics consider relationships among variables that univariate statistics cannot detect, generalizability theory considers relationships of error measurement that classical theory cannot. An extensive discussion of the concept of reliability and its use in classical test theory and generalizability theory is presented. A comparison of classical test theory and generalizability theory illustrates how generalizability theory subsumes all other reliability estimates as special cases. A hypothetical data set provides examples of when the failure to use generalizability theory can lead to seriously erroneous estimates of test reliability. The framework of generalizability theory incorporates two stages of analysis: (1) a generalizability study; and (2) a decision study. The former analyzes the extent to which results are generalizable to a population, while the latter uses information from the generalizability study to determine other generalizability coefficients for variations of the measurement protocol. Six data tables are provided, and an appendix presents the GENOVA program code used. (TJH) | ||
| 650 | 0 | 7 | |a Comparative Analysis. |2 ericd. |
| 650 | 1 | 7 | |a Generalizability Theory. |2 ericd. |
| 650 | 0 | 7 | |a Test Reliability. |2 ericd. |
| 650 | 1 | 7 | |a Test Theory. |2 ericd. |
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