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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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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. |
format | Online Article Text |
id | pubmed-6416874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT janshowli samplesizecalculationsformodelvalidationinlinearregressionanalysis AT shiehgwowen samplesizecalculationsformodelvalidationinlinearregressionanalysis |