Cargando…

Polychoric Correlation With Ordinal Data in Nursing Research

Measures in nursing research frequently use Likert scales that yield ordinal data. Confirmatory factor analysis using Pearson correlations commonly applies to such data, although this violates ordinal scale assumptions. OBJECTIVES: The aim of this study was to illustrate the application of polychori...

Descripción completa

Detalles Bibliográficos
Autores principales: Kiwanuka, Frank, Kopra, Juho, Sak-Dankosky, Natalia, Nanyonga, Rose Clarke, Kvist, Tarja
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617753/
https://www.ncbi.nlm.nih.gov/pubmed/35997708
http://dx.doi.org/10.1097/NNR.0000000000000614
_version_ 1784820912557654016
author Kiwanuka, Frank
Kopra, Juho
Sak-Dankosky, Natalia
Nanyonga, Rose Clarke
Kvist, Tarja
author_facet Kiwanuka, Frank
Kopra, Juho
Sak-Dankosky, Natalia
Nanyonga, Rose Clarke
Kvist, Tarja
author_sort Kiwanuka, Frank
collection PubMed
description Measures in nursing research frequently use Likert scales that yield ordinal data. Confirmatory factor analysis using Pearson correlations commonly applies to such data, although this violates ordinal scale assumptions. OBJECTIVES: The aim of this study was to illustrate the application of polychoric correlations and polychoric confirmatory factor analysis as a valid alternative statistical approach using data on family members’ perceived support from nurses as an exemplar. METHODS: A primary analysis of cross-sectional data from a sample of 800 participants using data collected with the Iceland-Family Perceived Support Questionnaire was conducted using polychoric versus Pearson correlations, analysis of variance, and confirmatory factor analysis. RESULTS: A two-factor measurement model was compatible with data from family members in the Ugandan care settings. Two contextual factors (cognitive and emotional support) constituted the family support measurement model. A factor correlation indicated that the two factors reflected distinct but closely related aspects of family support. Polychoric correlation revealed 13.8% (range: 5.5%–25.2%) higher correlations compared to Pearson correlations. Moreover, the polychoric agreed with the data, whereas the Pearson confirmatory factor analysis did not fit based on multiple statistical criteria. Analyses indicated a difference in emotional and cognitive support perception across two family characteristics: education and relationship to the patient. DISCUSSION: A polychoric correlation suggests stronger associations, and consequently, the approach can be more credible with an ordinal Likert scale than Pearson correlations. Hence, polychoric confirmatory factor analysis can address a larger proportion of variance. In nursing research, polychoric confirmatory factor analysis can confidently be utilized when conducting confirmatory factor analysis of ordinal variables in Likert scales. Furthermore, when a Pearson confirmatory factor analysis is used for ordinal Likert scales, the researcher should carefully evaluate the difference between the two approaches and justify their methodological choice. Even though we do not suggest dispensing with Pearson correlations entirely, we recommend using polychoric correlation for ordinal Likert scales.
format Online
Article
Text
id pubmed-9617753
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Lippincott Williams & Wilkins
record_format MEDLINE/PubMed
spelling pubmed-96177532022-11-14 Polychoric Correlation With Ordinal Data in Nursing Research Kiwanuka, Frank Kopra, Juho Sak-Dankosky, Natalia Nanyonga, Rose Clarke Kvist, Tarja Nurs Res Methods Measures in nursing research frequently use Likert scales that yield ordinal data. Confirmatory factor analysis using Pearson correlations commonly applies to such data, although this violates ordinal scale assumptions. OBJECTIVES: The aim of this study was to illustrate the application of polychoric correlations and polychoric confirmatory factor analysis as a valid alternative statistical approach using data on family members’ perceived support from nurses as an exemplar. METHODS: A primary analysis of cross-sectional data from a sample of 800 participants using data collected with the Iceland-Family Perceived Support Questionnaire was conducted using polychoric versus Pearson correlations, analysis of variance, and confirmatory factor analysis. RESULTS: A two-factor measurement model was compatible with data from family members in the Ugandan care settings. Two contextual factors (cognitive and emotional support) constituted the family support measurement model. A factor correlation indicated that the two factors reflected distinct but closely related aspects of family support. Polychoric correlation revealed 13.8% (range: 5.5%–25.2%) higher correlations compared to Pearson correlations. Moreover, the polychoric agreed with the data, whereas the Pearson confirmatory factor analysis did not fit based on multiple statistical criteria. Analyses indicated a difference in emotional and cognitive support perception across two family characteristics: education and relationship to the patient. DISCUSSION: A polychoric correlation suggests stronger associations, and consequently, the approach can be more credible with an ordinal Likert scale than Pearson correlations. Hence, polychoric confirmatory factor analysis can address a larger proportion of variance. In nursing research, polychoric confirmatory factor analysis can confidently be utilized when conducting confirmatory factor analysis of ordinal variables in Likert scales. Furthermore, when a Pearson confirmatory factor analysis is used for ordinal Likert scales, the researcher should carefully evaluate the difference between the two approaches and justify their methodological choice. Even though we do not suggest dispensing with Pearson correlations entirely, we recommend using polychoric correlation for ordinal Likert scales. Lippincott Williams & Wilkins 2022 2022-08-20 /pmc/articles/PMC9617753/ /pubmed/35997708 http://dx.doi.org/10.1097/NNR.0000000000000614 Text en Copyright © 2022 The Authors. Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods
Kiwanuka, Frank
Kopra, Juho
Sak-Dankosky, Natalia
Nanyonga, Rose Clarke
Kvist, Tarja
Polychoric Correlation With Ordinal Data in Nursing Research
title Polychoric Correlation With Ordinal Data in Nursing Research
title_full Polychoric Correlation With Ordinal Data in Nursing Research
title_fullStr Polychoric Correlation With Ordinal Data in Nursing Research
title_full_unstemmed Polychoric Correlation With Ordinal Data in Nursing Research
title_short Polychoric Correlation With Ordinal Data in Nursing Research
title_sort polychoric correlation with ordinal data in nursing research
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617753/
https://www.ncbi.nlm.nih.gov/pubmed/35997708
http://dx.doi.org/10.1097/NNR.0000000000000614
work_keys_str_mv AT kiwanukafrank polychoriccorrelationwithordinaldatainnursingresearch
AT koprajuho polychoriccorrelationwithordinaldatainnursingresearch
AT sakdankoskynatalia polychoriccorrelationwithordinaldatainnursingresearch
AT nanyongaroseclarke polychoriccorrelationwithordinaldatainnursingresearch
AT kvisttarja polychoriccorrelationwithordinaldatainnursingresearch