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Generalizability of scores influenced by multiple sources of variance

Generalizability of scores influenced by multiple sources of variance Abstract Generalizability theory concerns the adequacy with which a “universe” score can be inferred from a set of observations. In this paper the theory is applied to a universe in which observations are classifiable according to two independent variable aspects of the measuring procedure. Several types of universe scores are developed and the variance components ascertained for each type. The composition of expected observed-score variance and the adequacy of inference to a particular type of universe score is a function of the procedure used in gathering data. A generalizability study provides estimates of variance components which can be used in designing an efficient procedure for a particular decision purpose. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Psychometrika Springer Journals

Generalizability of scores influenced by multiple sources of variance

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References (20)

Publisher
Springer Journals
Copyright
1965 Psychometric Society
ISSN
0033-3123
eISSN
1860-0980
DOI
10.1007/BF02289531
Publisher site
See Article on Publisher Site

Abstract

Abstract Generalizability theory concerns the adequacy with which a “universe” score can be inferred from a set of observations. In this paper the theory is applied to a universe in which observations are classifiable according to two independent variable aspects of the measuring procedure. Several types of universe scores are developed and the variance components ascertained for each type. The composition of expected observed-score variance and the adequacy of inference to a particular type of universe score is a function of the procedure used in gathering data. A generalizability study provides estimates of variance components which can be used in designing an efficient procedure for a particular decision purpose.

Journal

PsychometrikaSpringer Journals

Published: Dec 1, 1965

Keywords: Psychometrics; Assessment, Testing and Evaluation; Statistics for Social Sciences, Humanities, Law; Statistical Theory and Methods

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