by Research and Development Division, American College Testing Program in Iowa City, Iowa .
Written in English
|Statement||Robert L. Brennan.|
|Series||ACT technical bulletin -- no. 30|
|Contributions||American College Testing Program. Research and Development Division., Navy Personnel Research and Development Center.|
|The Physical Object|
|Pagination||xii, 140 p. :|
|Number of Pages||140|
H.W. Marsh, L.F. Scalas, in International Encyclopedia of Education (Third Edition), Extensions of the REM. In their review of theoretical and empirical support for the REM, Marsh et al. (; also see Marsh and Craven ()) argued for the need for further research to test the generalizability of the REM over nationality and culture (support was based largely on studies done in. Generalizability theory recognizes that the universe of admissible observations encompassed by a G study may be broader than the universe to which a decision maker wishes to generalize in a D study, the universe of generalization. The Use of Generalizability Theory for Assessing Relations among Items within Domains in Diagnostic Testing George B. Macready University of Maryland The purpose of this study was to describe a proce- dure based on generalizability theory for assessing the adequacy of item groupings generated by means of a domain-referenced testing procedure is. Generalizability theory (see Cronbach, Gleser, Nanda, & Rajaratnam, ) is a useful statistical approach, rarely used in qualitative research in management, that can be used to explain variance.
18 GENERALIZABILITY THEORY GEORGE A. MARCOULIDES Department of Management Science, California State University at Fullerton, Fullerton, California I. INTRODUCTION Generalizability theory is a random sampling theory for examining the dependability of measurement procedures that has been heralded by many psychometricians as "the most broadly defined psychometric model cur- rently in . Restriction of range (in this case, most likely due to developmental similarities on the particular items in the and year-old sample) and corresponding problems related to reliability or generalizability of test scores are common and understudied problems in psychological testing (Thorndike, ; Wiberg & Sundstrom, ).Cited by: 9. It is argued in this paper that generalizability theory provides a uniquely useful framework for defining and quantifying the dependability of data for decision making. It does so by requiring careful specification of the conditions of measurement and the anticipated sources of variation in the results of the measurement procedure. A distinction is made between generalizability (G) studies and. Brennan, Robert L. (), “ Extensions of Generalizability Theory to Domain Referenced Testing,” ACT Technical Bulletin No. 30 (June). Iowa City, IA: American College Testing Program, p. Cited by:
Full text of "ERIC ED Why Generalizability Theory Yields Better Results than Classical Test other formats DOCUMENT RESUME ED TM AUTHOR TITLE PUB DATE NOTE PUB TYPE EDRS PRICE DESCRIPTORS IDENTIFIERS Eason, Sandra Why Generalizability Theory Yields Better Results than Classical Test Theory. Special education has criticized many norm-referenced tests for their lack of demonstrated reliability with exceptional populations. Current advocacy of using criterion-referenced tests with handicapped persons has failed to consider the lack of empirical data on their by: 9. Corrections and Some Additions/Comments for Generalizability Theory Robert L. Brennan August 9, The following is a list of known errors in Brennan (), as well as a small number of additions or comments. † P Title of Table should say \D Study I:p Design" † P 17 lines from bottom of page. add \(See also Kane. Rating scales form an important means of gathering evaluation data. Since important decisions are often based on these evaluations, determining the reliability of rating data can be critical. Most commonly used methods of estimating reliability require a complete set of ratings i.e. every subject being rated must be rated by each judge. Over fifty years ago Ebel described an algorithm for Cited by: