[RsR] Welcome to the "R-SIG-Robust" mailing list (Digest mode)
Dear R community, We analyzed a series of biological samples and obtained results for 60 primary metabolites. For some metabolites, the results are in absolute concentration units, and for others, in relative units, because they were measured using different machines. The goal is to build a predictive model that selects a small number of metabolites, which can then be measured on one machine to predict a rate associated with each sample. Each sample has a different regeneration rate. In total, 13 samples were analyzed, each with biological and technical replicates. First, I performed a forward stepwise regression. Then, I was advised to perform a Leave-One-Out Cross-Validation (LOOCV). I have done this in R, but I am not sure if it is correct, because the resulting predictive model contains only one metabolite. I would like guidance from the R community on whether my approach and LOOCV implementation are appropriate given this small dataset and the type of data I have. I can provide the R documents and scripts I used so that members can review them and advise whether the analysis is correct. Any suggestions or recommendations would be greatly appreciated. Thank you very much for your time and help. Best regards, Teresa
De: R-SIG-Robust <r-sig-robust-bounces at r-project.org> en nombre de r-sig-robust-request at r-project.org <r-sig-robust-request at r-project.org>
Enviado: martes, 14 de octubre de 2025 13:16 Para: Teresa P?rez-Pi?ar L?pez <tperezpi at uax.es> Asunto: Welcome to the "R-SIG-Robust" mailing list (Digest mode) PRECAUCI?N: Este correo electr?nico se origin? fuera de la organizaci?n. No abra enlaces ni archivos adjuntos a menos que pueda confirmar que el remitente es conocido y que el contenido es seguro Welcome to the R-SIG-Robust at r-project.org mailing list! To post to this list, send your message to: r-sig-robust at r-project.org General information about the mailing list is at: https://stat.ethz.ch/mailman/listinfo/r-sig-robust If you ever want to unsubscribe or change your options (eg, switch to or from digest mode, change your password, etc.), visit your subscription page at: https://stat.ethz.ch/mailman/options/r-sig-robust/tperezpi%40uax.es You can also make such adjustments via email by sending a message to: R-SIG-Robust-request at r-project.org with the word `help' in the subject or body (don't include the quotes), and you will get back a message with instructions. You must know your password to change your options (including changing the password, itself) or to unsubscribe without confirmation. It is: 110902 Normally, Mailman will remind you of your r-project.org mailing list passwords once every month, although you can disable this if you prefer. This reminder will also include instructions on how to unsubscribe or change your account options. There is also a button on your options page that will email your current password to you. CL?USULA DE CONFIDENCIALIDAD Este mensaje ha sido generado desde una cuenta de la Universidad Alfonso X el Sabio para los fines propios de la instituci?n. Su contenido se considera confidencial y, salvo que la naturaleza del mismo as? lo exija, no est? permitida su reproducci?n o distribuci?n sin la autorizaci?n expresa. Si Usted ha recibido indebidamente este correo le rogamos que advierta de ello al remitente y proceda a su eliminaci?n. Pol?tica de privacidad www.uax.com/politica-de-privacidad -------------- next part -------------- An HTML attachment was scrubbed... URL: <https://stat.ethz.ch/pipermail/r-sig-robust/attachments/20251014/f3468ec0/attachment.html> -------------- next part -------------- A non-text attachment was scrubbed... Name: Regression model development_raw data_bueno.pdf Type: application/pdf Size: 77506 bytes Desc: Regression model development_raw data_bueno.pdf URL: <https://stat.ethz.ch/pipermail/r-sig-robust/attachments/20251014/f3468ec0/attachment.pdf>