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LADES: A Software for Constructing and Analyzing Longitudinal Designs in Biomedical Research
One of the most important steps in biomedical longitudinal studies is choosing a good experimental design that can provide high accuracy in the analysis of results with a minimum sample size. Several methods for constructing efficient longitudinal designs have been developed based on power analysis...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4077564/ https://www.ncbi.nlm.nih.gov/pubmed/24983945 http://dx.doi.org/10.1371/journal.pone.0100570 |
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author | Vázquez-Alcocer, Alan Garzón-Cortes, Daniel Ladislao Sánchez-Casas, Rosa María |
author_facet | Vázquez-Alcocer, Alan Garzón-Cortes, Daniel Ladislao Sánchez-Casas, Rosa María |
author_sort | Vázquez-Alcocer, Alan |
collection | PubMed |
description | One of the most important steps in biomedical longitudinal studies is choosing a good experimental design that can provide high accuracy in the analysis of results with a minimum sample size. Several methods for constructing efficient longitudinal designs have been developed based on power analysis and the statistical model used for analyzing the final results. However, development of this technology is not available to practitioners through user-friendly software. In this paper we introduce LADES (Longitudinal Analysis and Design of Experiments Software) as an alternative and easy-to-use tool for conducting longitudinal analysis and constructing efficient longitudinal designs. LADES incorporates methods for creating cost-efficient longitudinal designs, unequal longitudinal designs, and simple longitudinal designs. In addition, LADES includes different methods for analyzing longitudinal data such as linear mixed models, generalized estimating equations, among others. A study of European eels is reanalyzed in order to show LADES capabilities. Three treatments contained in three aquariums with five eels each were analyzed. Data were collected from 0 up to the 12th week post treatment for all the eels (complete design). The response under evaluation is sperm volume. A linear mixed model was fitted to the results using LADES. The complete design had a power of 88.7% using 15 eels. With LADES we propose the use of an unequal design with only 14 eels and 89.5% efficiency. LADES was developed as a powerful and simple tool to promote the use of statistical methods for analyzing and creating longitudinal experiments in biomedical research. |
format | Online Article Text |
id | pubmed-4077564 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-40775642014-07-03 LADES: A Software for Constructing and Analyzing Longitudinal Designs in Biomedical Research Vázquez-Alcocer, Alan Garzón-Cortes, Daniel Ladislao Sánchez-Casas, Rosa María PLoS One Research Article One of the most important steps in biomedical longitudinal studies is choosing a good experimental design that can provide high accuracy in the analysis of results with a minimum sample size. Several methods for constructing efficient longitudinal designs have been developed based on power analysis and the statistical model used for analyzing the final results. However, development of this technology is not available to practitioners through user-friendly software. In this paper we introduce LADES (Longitudinal Analysis and Design of Experiments Software) as an alternative and easy-to-use tool for conducting longitudinal analysis and constructing efficient longitudinal designs. LADES incorporates methods for creating cost-efficient longitudinal designs, unequal longitudinal designs, and simple longitudinal designs. In addition, LADES includes different methods for analyzing longitudinal data such as linear mixed models, generalized estimating equations, among others. A study of European eels is reanalyzed in order to show LADES capabilities. Three treatments contained in three aquariums with five eels each were analyzed. Data were collected from 0 up to the 12th week post treatment for all the eels (complete design). The response under evaluation is sperm volume. A linear mixed model was fitted to the results using LADES. The complete design had a power of 88.7% using 15 eels. With LADES we propose the use of an unequal design with only 14 eels and 89.5% efficiency. LADES was developed as a powerful and simple tool to promote the use of statistical methods for analyzing and creating longitudinal experiments in biomedical research. Public Library of Science 2014-07-01 /pmc/articles/PMC4077564/ /pubmed/24983945 http://dx.doi.org/10.1371/journal.pone.0100570 Text en © 2014 Vázquez-Alcocer et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Vázquez-Alcocer, Alan Garzón-Cortes, Daniel Ladislao Sánchez-Casas, Rosa María LADES: A Software for Constructing and Analyzing Longitudinal Designs in Biomedical Research |
title | LADES: A Software for Constructing and Analyzing Longitudinal Designs in Biomedical Research |
title_full | LADES: A Software for Constructing and Analyzing Longitudinal Designs in Biomedical Research |
title_fullStr | LADES: A Software for Constructing and Analyzing Longitudinal Designs in Biomedical Research |
title_full_unstemmed | LADES: A Software for Constructing and Analyzing Longitudinal Designs in Biomedical Research |
title_short | LADES: A Software for Constructing and Analyzing Longitudinal Designs in Biomedical Research |
title_sort | lades: a software for constructing and analyzing longitudinal designs in biomedical research |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4077564/ https://www.ncbi.nlm.nih.gov/pubmed/24983945 http://dx.doi.org/10.1371/journal.pone.0100570 |
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