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Methods for Identifying Biased Test Items (Measurement Methods for the Social Science) download ebook

by Professor Lorrie Ann Shepard,Gregory Camilli

Methods for Identifying Biased Test Items (Measurement Methods for the Social Science) download ebook
ISBN:
0803944160
ISBN13:
978-0803944169
Author:
Professor Lorrie Ann Shepard,Gregory Camilli
Publisher:
Sage Publications, Inc; 1 edition (April 6, 1994)
Language:
Pages:
192 pages
ePUB:
1466 kb
Fb2:
1727 kb
Other formats:
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Category:
Mathematics
Subcategory:
Rating:
4.5

Start by marking Methods for Identifying Biased Test Items as Want to. .Advice is provided on the most useful methods for particular test situations.

Start by marking Methods for Identifying Biased Test Items as Want to Read: Want to Read savin. ant to Read.

Measurement Methods for the Social Science. By (author) Gregory Camilli, By (author) Lorrie Shepard. The authors explain the logic of each method - from item-response theory to nonparametric, categorical methods - in terms of how differential item functioning (DIF) is defined by the method and how well the method can be expected to work. A summary of findings on the behaviour of indices in empirical studies is included.

Introduction Test Bias, Item Bias, and Test Validity Early Item Bias Indices Based on Classical Test Theory . oceedings{, title {Methods for Identifying Biased Test Items}, author {Gregory Camilli and Lorrie A. Shepard}, year {1994} }.

Introduction Test Bias, Item Bias, and Test Validity Early Item Bias Indices Based on Classical Test Theory and Analysis of Variance Item Response Theory as Applied to Differential Item Functioning Contingency Table Approaches Interpretations of Bias from DIF Statistics Conclusions and Caveats. Gregory Camilli, Lorrie A. Shepard.

by Gregory Camilli and Lorrie Ann Shepard. Select Format: Hardcover. ISBN13:9780803944169.

Series: Measurement Methods for the Social Science. With this book on item bias detection methods, Gregory Camilli and Lorrie Shepard have achieved this goal admirably

Series: Measurement Methods for the Social Science. April 1994 181 pages SAGE Publications, Inc. Download flyer Recommend to Library. With this book on item bias detection methods, Gregory Camilli and Lorrie Shepard have achieved this goal admirably.

Fundamentals of Item Response Theory (Measurement Methods for the Social Science) by Ronald K. Hambleton .

Fundamentals of Item Response Theory (Measurement Methods for the Social Science) Paperback. Series: Measurement Methods for the Social Science (Book 1).

Methods for Identifying Biased Test Items

Methods for Identifying Biased Test Items. This paper explores possible reasons for the gap, including test bias, variability in scores, the timed nature of the test, and environmental factors. When the SAT-M is used as the sole criterion for admission, gender differences in scores mean that disparate numbers of boys and girls are identified for high-level mathematics and science programs.

test items Thousand from ENG 102 at Kmm College Of Arts & Science. London: Falmer Press.

Camilli G Shepard L 1994 Methods for identifying biased test items Thousand from ENG 102 at Kmm College Of Arts & Science. In R. K. Hambleton, P. F. Merenda, & C. D. Spielberger (Ed., Adapting educational and psychological tests for cross-cultural assessment (pp. 139–169). Mahwah, NJ: Erl- baum.

Methods for identifying biased test items. G Camilli, LA Shepard. LA Shepard, LA Sheppard. Educational Measurement: Issues and Practice 16 (2), 5-24, 1997. Sage Publications, Inc, 1994.

This book makes clear to researchers what item-bias methods can (and cannot) do, how they work and how they should be interpreted. Advice is provided on the most useful methods for particular test situations. The authors explain the logic of each method - from item-response theory to nonparametric, categorical methods - in terms of how differential item functioning (DIF) is defined by the method and how well the method can be expected to work. A summary of findings on the behaviour of indices in empirical studies is included. The book concludes with a set of principles for deciding when DIF should be interpreted as evidence of bias.