ERandrinopoulou
commented
11 months ago Dear Qian,
Thank you for your interest in my work. Unfortunately, it is not possible yet to obtain individualized dynamic prediction in the latent class joint model. This will be an interesting addition to the method.
Kind regards, Eleni-Rosalina Andrinopoulou
Dr. E.R (Eleni-Rosalina) Andrinopoulou Assistant professor Biostatistics
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From: Yeqian227 @.> Sent: 02 November 2023 08:41 To: ERandrinopoulou/LatentClassJM @.> Cc: Subscribed @.***> Subject: [ERandrinopoulou/LatentClassJM] Dynamic Predictions in Bayesian Shared Parameter Joint Model with Latent Classes (Issue #1)
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Hi Eleni-Rosalina,
Thank you for your work! I have a question regarding the integration of latent classes in the Bayesian shared parameter joint model. Is it possible to obtain individual dynamic predictions in this context, and if so, how can it be done?
As far as I understand, the lcmm package allows for dynamic predictions of individuals based on their observed values up to a landmark, and joint models that do not include latent classes also support individual dynamic predictions. However, I'm interested in performing dynamic predictions within the framework of a Joint Model that includes latent classes.
Any guidance or insights you can provide on this matter would be greatly appreciated.
Thank you for your time.
Best , Qian
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Yeqian227
Hi Eleni-Rosalina,
Thank you for your work! I have a question regarding the integration of latent classes in the Bayesian shared parameter joint model. Is it possible to obtain individual dynamic predictions in this context, and if so, how can it be done?
As far as I understand, the
lcmmpackage allows for dynamic predictions of individuals based on their observed values up to a landmark, and joint models that do not include latent classes also support individual dynamic predictions. However, I'm interested in performing dynamic predictions within the framework of a Joint Model that includes latent classes.Any guidance or insights you can provide on this matter would be greatly appreciated.
Thank you for your time.
Best , Qian