Literature DB >> 17937841

Reporting subscores for institutions.

Shelby Haberman1, Sandip Sinharay, Gautam Puhan.   

Abstract

Recently, there has been an increasing level of interest in reporting subscores for components of larger assessments. This paper examines the issue of reporting subscores at an aggregate level, especially at the level of institutions to which the examinees belong. A new statistical approach based on classical test theory is proposed to assess when subscores at the institutional level have any added value over the total scores. The methods are applied to two operational data sets. For the data under study, the observed results provide little support in favour of reporting subscores for either examinees or institutions.

Mesh:

Year:  2007        PMID: 17937841     DOI: 10.1348/000711007X248875

Source DB:  PubMed          Journal:  Br J Math Stat Psychol        ISSN: 0007-1102            Impact factor:   3.380


  3 in total

1.  Penalized Best Linear Prediction of True Test Scores.

Authors:  Lili Yao; Shelby J Haberman; Mo Zhang
Journal:  Psychometrika       Date:  2018-09-21       Impact factor: 2.500

2.  Combining item response theory and diagnostic classification models: a psychometric model for scaling ability and diagnosing misconceptions.

Authors:  Laine Bradshaw; Jonathan Templin
Journal:  Psychometrika       Date:  2013-08-02       Impact factor: 2.500

3.  Classification Accuracy of Mixed Format Tests: A Bi-Factor Item Response Theory Approach.

Authors:  Wei Wang; Fritz Drasgow; Liwen Liu
Journal:  Front Psychol       Date:  2016-02-29
  3 in total

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