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Let Continuous Outcome Variables Remain Continuous
The complementary log-log is an alternative to logistic model. In many areas of research, the outcome data are continuous. We aim to provide a procedure that allows the researcher to estimate the coefficients of the complementary log-log model without dichotomizing and without loss of information. W...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3368309/ https://www.ncbi.nlm.nih.gov/pubmed/22693539 http://dx.doi.org/10.1155/2012/639124 |
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author | Bakhshi, Enayatollah McArdle, Brian Mohammad, Kazem Seifi, Behjat Biglarian, Akbar |
author_facet | Bakhshi, Enayatollah McArdle, Brian Mohammad, Kazem Seifi, Behjat Biglarian, Akbar |
author_sort | Bakhshi, Enayatollah |
collection | PubMed |
description | The complementary log-log is an alternative to logistic model. In many areas of research, the outcome data are continuous. We aim to provide a procedure that allows the researcher to estimate the coefficients of the complementary log-log model without dichotomizing and without loss of information. We show that the sample size required for a specific power of the proposed approach is substantially smaller than the dichotomizing method. We find that estimators derived from proposed method are consistently more efficient than dichotomizing method. To illustrate the use of proposed method, we employ the data arising from the NHSI. |
format | Online Article Text |
id | pubmed-3368309 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-33683092012-06-12 Let Continuous Outcome Variables Remain Continuous Bakhshi, Enayatollah McArdle, Brian Mohammad, Kazem Seifi, Behjat Biglarian, Akbar Comput Math Methods Med Research Article The complementary log-log is an alternative to logistic model. In many areas of research, the outcome data are continuous. We aim to provide a procedure that allows the researcher to estimate the coefficients of the complementary log-log model without dichotomizing and without loss of information. We show that the sample size required for a specific power of the proposed approach is substantially smaller than the dichotomizing method. We find that estimators derived from proposed method are consistently more efficient than dichotomizing method. To illustrate the use of proposed method, we employ the data arising from the NHSI. Hindawi Publishing Corporation 2012 2012-05-29 /pmc/articles/PMC3368309/ /pubmed/22693539 http://dx.doi.org/10.1155/2012/639124 Text en Copyright © 2012 Enayatollah Bakhshi et al. 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 Bakhshi, Enayatollah McArdle, Brian Mohammad, Kazem Seifi, Behjat Biglarian, Akbar Let Continuous Outcome Variables Remain Continuous |
title | Let Continuous Outcome Variables Remain Continuous |
title_full | Let Continuous Outcome Variables Remain Continuous |
title_fullStr | Let Continuous Outcome Variables Remain Continuous |
title_full_unstemmed | Let Continuous Outcome Variables Remain Continuous |
title_short | Let Continuous Outcome Variables Remain Continuous |
title_sort | let continuous outcome variables remain continuous |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3368309/ https://www.ncbi.nlm.nih.gov/pubmed/22693539 http://dx.doi.org/10.1155/2012/639124 |
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