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The Assignment of Scores Procedure for Ordinal Categorical Data
Ordinal data are the most frequently encountered type of data in the social sciences. Many statistical methods can be used to process such data. One common method is to assign scores to the data, convert them into interval data, and further perform statistical analysis. There are several authors who...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4176904/ https://www.ncbi.nlm.nih.gov/pubmed/25295296 http://dx.doi.org/10.1155/2014/304213 |
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author | Chen, Han-Ching Wang, Nae-Sheng |
author_facet | Chen, Han-Ching Wang, Nae-Sheng |
author_sort | Chen, Han-Ching |
collection | PubMed |
description | Ordinal data are the most frequently encountered type of data in the social sciences. Many statistical methods can be used to process such data. One common method is to assign scores to the data, convert them into interval data, and further perform statistical analysis. There are several authors who have recently developed assigning score methods to assign scores to ordered categorical data. This paper proposes an approach that defines an assigning score system for an ordinal categorical variable based on underlying continuous latent distribution with interpretation by using three case study examples. The results show that the proposed score system is well for skewed ordinal categorical data. |
format | Online Article Text |
id | pubmed-4176904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-41769042014-10-07 The Assignment of Scores Procedure for Ordinal Categorical Data Chen, Han-Ching Wang, Nae-Sheng ScientificWorldJournal Research Article Ordinal data are the most frequently encountered type of data in the social sciences. Many statistical methods can be used to process such data. One common method is to assign scores to the data, convert them into interval data, and further perform statistical analysis. There are several authors who have recently developed assigning score methods to assign scores to ordered categorical data. This paper proposes an approach that defines an assigning score system for an ordinal categorical variable based on underlying continuous latent distribution with interpretation by using three case study examples. The results show that the proposed score system is well for skewed ordinal categorical data. Hindawi Publishing Corporation 2014 2014-09-11 /pmc/articles/PMC4176904/ /pubmed/25295296 http://dx.doi.org/10.1155/2014/304213 Text en Copyright © 2014 H.-C. Chen and N.-S. Wang. https://creativecommons.org/licenses/by/3.0/ 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. |
spellingShingle | Research Article Chen, Han-Ching Wang, Nae-Sheng The Assignment of Scores Procedure for Ordinal Categorical Data |
title | The Assignment of Scores Procedure for Ordinal Categorical Data |
title_full | The Assignment of Scores Procedure for Ordinal Categorical Data |
title_fullStr | The Assignment of Scores Procedure for Ordinal Categorical Data |
title_full_unstemmed | The Assignment of Scores Procedure for Ordinal Categorical Data |
title_short | The Assignment of Scores Procedure for Ordinal Categorical Data |
title_sort | assignment of scores procedure for ordinal categorical data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4176904/ https://www.ncbi.nlm.nih.gov/pubmed/25295296 http://dx.doi.org/10.1155/2014/304213 |
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