Data analysis based on SISSREM: Shiny Interactive, Supervised and Systematic report from REpeated Measures data
Longitudinal methods are the procedures of choice for scientists who see their phenomena of interest as dynamic. However, given the difficulty of using linear mixed models (LMM), other simpler approaches are used, but suboptimal and sometimes discouraged by the structure of the data. The objective o...
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| Formato: | tesis de maestría |
| Fecha de publicación: | 2019 |
| País: | España |
| Recursos: | Universitat Oberta de Catalunya (UOC) |
| Repositorio: | O2, repositorio institucional de la UOC |
| OAI Identifier: | oai:openaccess.uoc.edu:10609/98186 |
| Acesso em linha: | http://hdl.handle.net/10609/98186 |
| Access Level: | acceso abierto |
| Palavra-chave: | repeated measures linear mixed model Shiny app medidas repetidas modelo lineal mixto aplicación Shiny mesures repetides model lineal mixt aplicació Shiny Bioinformatics -- TFM Bioinformàtica -- TFM Bioinformática -- TFM |
| Resumo: | Longitudinal methods are the procedures of choice for scientists who see their phenomena of interest as dynamic. However, given the difficulty of using linear mixed models (LMM), other simpler approaches are used, but suboptimal and sometimes discouraged by the structure of the data. The objective of this work is to develop a systematic and supervised methodology so that biomedical researchers with low-average level of statistics can perform an analysis of repeated measures. By using R programming language, we have developed a Shiny online application named SISSREM (Shiny Interactive, Supervised and Systematic report from REpeated Measures data). It can: i) instruct the user in the understanding of a LMM analysis for repeated measures with an example database; ii) allow the user to analyze their own data; and iii) allow the user to create an interactive, supervised and systematic report to be exported from the Shiny application. The main core of the application consists of a guided tour through a predetermined analysis with a sample database and the systematic decisions that should be made in an LMM analysis. Therefore, it has been structured in different modules that allow you to explore and process the data, as well as perform the LMM analysis, save data and/or generate a report in .PDF, .HTML or .DOCX format.SISSREM (https://sissrem.shinyapps.io/SISSREM_v1/) is a functional application whose objective is to simplify the use and disseminate the usefulness of LMM in biomedical research. |
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