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Sample size calculations for model validation in linear regression analysis

BACKGROUND: Linear regression analysis is a widely used statistical technique in practical applications. For planning and appraising validation studies of simple linear regression, an approximate sample size formula has been proposed for the joint test of intercept and slope coefficients. METHODS: T...

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Detalles Bibliográficos
Autores principales: Jan, Show-Li, Shieh, Gwowen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6416874/
https://www.ncbi.nlm.nih.gov/pubmed/30866825
http://dx.doi.org/10.1186/s12874-019-0697-9
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author Jan, Show-Li
Shieh, Gwowen
author_facet Jan, Show-Li
Shieh, Gwowen
author_sort Jan, Show-Li
collection PubMed
description BACKGROUND: Linear regression analysis is a widely used statistical technique in practical applications. For planning and appraising validation studies of simple linear regression, an approximate sample size formula has been proposed for the joint test of intercept and slope coefficients. METHODS: The purpose of this article is to reveal the potential drawback of the existing approximation and to provide an alternative and exact solution of power and sample size calculations for model validation in linear regression analysis. RESULTS: A fetal weight example is included to illustrate the underlying discrepancy between the exact and approximate methods. Moreover, extensive numerical assessments were conducted to examine the relative performance of the two distinct procedures. CONCLUSIONS: The results show that the exact approach has a distinct advantage over the current method with greater accuracy and high robustness. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12874-019-0697-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-64168742019-03-25 Sample size calculations for model validation in linear regression analysis Jan, Show-Li Shieh, Gwowen BMC Med Res Methodol Research Article BACKGROUND: Linear regression analysis is a widely used statistical technique in practical applications. For planning and appraising validation studies of simple linear regression, an approximate sample size formula has been proposed for the joint test of intercept and slope coefficients. METHODS: The purpose of this article is to reveal the potential drawback of the existing approximation and to provide an alternative and exact solution of power and sample size calculations for model validation in linear regression analysis. RESULTS: A fetal weight example is included to illustrate the underlying discrepancy between the exact and approximate methods. Moreover, extensive numerical assessments were conducted to examine the relative performance of the two distinct procedures. CONCLUSIONS: The results show that the exact approach has a distinct advantage over the current method with greater accuracy and high robustness. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12874-019-0697-9) contains supplementary material, which is available to authorized users. BioMed Central 2019-03-12 /pmc/articles/PMC6416874/ /pubmed/30866825 http://dx.doi.org/10.1186/s12874-019-0697-9 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Jan, Show-Li
Shieh, Gwowen
Sample size calculations for model validation in linear regression analysis
title Sample size calculations for model validation in linear regression analysis
title_full Sample size calculations for model validation in linear regression analysis
title_fullStr Sample size calculations for model validation in linear regression analysis
title_full_unstemmed Sample size calculations for model validation in linear regression analysis
title_short Sample size calculations for model validation in linear regression analysis
title_sort sample size calculations for model validation in linear regression analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6416874/
https://www.ncbi.nlm.nih.gov/pubmed/30866825
http://dx.doi.org/10.1186/s12874-019-0697-9
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