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Stats 2018, 1(1), 1-13; https://doi.org/10.3390/stats1010001

A Nonparametric Statistical Approach to Content Analysis of Items

1
Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo 05508-090, Brazil
2
Faculdade de Psicologia e de Ciências da Educação, Universidade de Coimbra, 3000-115 Coimbra, Portugal
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 6 December 2017 / Revised: 23 January 2018 / Accepted: 25 January 2018 / Published: 1 February 2018
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Abstract

In order to use psychometric instruments to assess a multidimensional construct, we may decompose it into dimensions and, in order to assess each dimension, develop a set of items, so one may assess the construct as a whole, by assessing its dimensions. In this scenario, content analysis of items aims to verify if the developed items are assessing the dimension they are supposed to by requesting the judgement of specialists in the studied construct about the dimension that the developed items assess. This paper aims to develop a nonparametric statistical approach based on the Cochran’s Q test to analyse the content of items in order to present a practical method to assess the consistency of the content analysis process; this is achieved by the development of a statistical test that seeks to determine if all the specialists have the same capability to judge the items. A simulation study is conducted to check the consistency of the test and it is applied to a real validation process. View Full-Text
Keywords: nonparametric statistics; applied statistics; content validity; psychometric instruments; psychometrics nonparametric statistics; applied statistics; content validity; psychometric instruments; psychometrics
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Marcondes, D.; Marcondes, N.R. A Nonparametric Statistical Approach to Content Analysis of Items. Stats 2018, 1, 1-13.

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