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Item response theory for measurement validity

Item response theory (IRT) is an important method of assessing the validity of measurement scales that is underutilized in the field of psychiatry. IRT describes the relationship between a latent trait (e.g., the construct that the scale proposes to assess), the properties of the items in the scale,...

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Autores principales: YANG, Frances M., KAO, Solon T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Shanghai Municipal Bureau of Publishing 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4118016/
https://www.ncbi.nlm.nih.gov/pubmed/25114494
http://dx.doi.org/10.3969/j.issn.1002-0829.2014.03.010
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author YANG, Frances M.
KAO, Solon T.
author_facet YANG, Frances M.
KAO, Solon T.
author_sort YANG, Frances M.
collection PubMed
description Item response theory (IRT) is an important method of assessing the validity of measurement scales that is underutilized in the field of psychiatry. IRT describes the relationship between a latent trait (e.g., the construct that the scale proposes to assess), the properties of the items in the scale, and respondents’ answers to the individual items. This paper introduces the basic premise, assumptions, and methods of IRT. To help explain these concepts we generate a hypothetical scale using three items from a modified, binary (yes/no) response version of the Center for Epidemiological Studies-Depression scale that was administered to 19,399 respondents. We first conducted a factor analysis to confirm the unidimensionality of the three items and then proceeded with Mplus software to construct the 2-Parameter Logic (2-PL) IRT model of the data, a method which allows for estimates of both item discrimination and item difficulty. The utility of this information both for clinical purposes and for scale construction purposes is discussed.
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spelling pubmed-41180162014-08-11 Item response theory for measurement validity YANG, Frances M. KAO, Solon T. Shanghai Arch Psychiatry Biostatistics in Psychiatry Item response theory (IRT) is an important method of assessing the validity of measurement scales that is underutilized in the field of psychiatry. IRT describes the relationship between a latent trait (e.g., the construct that the scale proposes to assess), the properties of the items in the scale, and respondents’ answers to the individual items. This paper introduces the basic premise, assumptions, and methods of IRT. To help explain these concepts we generate a hypothetical scale using three items from a modified, binary (yes/no) response version of the Center for Epidemiological Studies-Depression scale that was administered to 19,399 respondents. We first conducted a factor analysis to confirm the unidimensionality of the three items and then proceeded with Mplus software to construct the 2-Parameter Logic (2-PL) IRT model of the data, a method which allows for estimates of both item discrimination and item difficulty. The utility of this information both for clinical purposes and for scale construction purposes is discussed. Shanghai Municipal Bureau of Publishing 2014-06 /pmc/articles/PMC4118016/ /pubmed/25114494 http://dx.doi.org/10.3969/j.issn.1002-0829.2014.03.010 Text en Copyright © 2014 by Shanghai Municipal Bureau of Publishing http://creativecommons.org/licenses/by-nc-sa/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/
spellingShingle Biostatistics in Psychiatry
YANG, Frances M.
KAO, Solon T.
Item response theory for measurement validity
title Item response theory for measurement validity
title_full Item response theory for measurement validity
title_fullStr Item response theory for measurement validity
title_full_unstemmed Item response theory for measurement validity
title_short Item response theory for measurement validity
title_sort item response theory for measurement validity
topic Biostatistics in Psychiatry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4118016/
https://www.ncbi.nlm.nih.gov/pubmed/25114494
http://dx.doi.org/10.3969/j.issn.1002-0829.2014.03.010
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