drizopoulos / JMbayes

Joint Models for Longitudinal and Survival Data using MCMC
59 stars 24 forks source link

Multivariate LME #27

Closed GusDM closed 3 years ago

GusDM commented 5 years ago

Hi, Would it be possible to fit a second linear mixed effects model - with different dependent variable - instead of the time-to-event model? Thank you!

drizopoulos commented 5 years ago

Yes, using function mvglmer().

From: GusDM notifications@github.com<mailto:notifications@github.com> Date: Saturday, 12 Jan 2019, 23:53 To: drizopoulos/JMbayes JMbayes@noreply.github.com<mailto:JMbayes@noreply.github.com> Cc: Subscribed subscribed@noreply.github.com<mailto:subscribed@noreply.github.com> Subject: [drizopoulos/JMbayes] Multivariate LME (#27)

Hi, Would it be possible to fit a second linear mixed effects model - with different dependent variable - instead of the time-to-event model? Thank you!

— You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHubhttps://github.com/drizopoulos/JMbayes/issues/27, or mute the threadhttps://github.com/notifications/unsubscribe-auth/AMn5z7SSzjGpzC4KTFxL1N5f-cibbVkjks5vCmeAgaJpZM4Z840d.

sgachau commented 5 years ago

Dear Prof. Rizopoulos,

Thank you for JMbayes package which is very helpful. I am fitting a model with four longitudinal outcomes and since i don't have a time-to-event outcome am using function mvglmer() function. I would like to know whether this qualifies as a joint model. I would also like to know whether shared parameter assumption hold for mvglmer().

Thank you Sgachau

drizopoulos commented 5 years ago

Yes, this is also a joint model.

From: sgachau notifications@github.com<mailto:notifications@github.com> Date: Friday, 07 Jun 2019, 12:24 PM To: drizopoulos/JMbayes JMbayes@noreply.github.com<mailto:JMbayes@noreply.github.com> Cc: D. Rizopoulos d.rizopoulos@erasmusmc.nl<mailto:d.rizopoulos@erasmusmc.nl>, Comment comment@noreply.github.com<mailto:comment@noreply.github.com> Subject: Re: [drizopoulos/JMbayes] Multivariate LME (#27)

Dear Prof. Rizopoulos,

Thank you for JMbayes package which is very helpful. I am fitting a model with four longitudinal outcomes and since i don't have a time-to-event outcome am using function mvglmer() function. I would like to know whether this qualifies as a joint model. I would also like to know whether shared parameter assumption hold for mvglmer().

Thank you Sgachau

— You are receiving this because you commented. Reply to this email directly, view it on GitHubhttps://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fdrizopoulos%2FJMbayes%2Fissues%2F27%3Femail_source%3Dnotifications%26email_token%3DADE7TTYVRNQNANNSBZEBLZTPZIZNDA5CNFSM4GPTRUO2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGODXFOEPI%23issuecomment-499835453&data=02%7C01%7Cd.rizopoulos%40erasmusmc.nl%7Cc4e5e0821eb3469af0af08d6eb324c84%7C526638ba6af34b0fa532a1a511f4ac80%7C0%7C0%7C636954998601837294&sdata=K4eVAX1N6jSOUwBS1CVtcFBdkL8pOlEqXkVboppI2Ys%3D&reserved=0, or mute the threadhttps://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-auth%2FADE7TT6SHGTLUNRISQ5OHL3PZIZNDANCNFSM4GPTRUOQ&data=02%7C01%7Cd.rizopoulos%40erasmusmc.nl%7Cc4e5e0821eb3469af0af08d6eb324c84%7C526638ba6af34b0fa532a1a511f4ac80%7C0%7C0%7C636954998601847306&sdata=pY26H7PhtVVvWO%2FyhsTaruU4mTIsP7KCGQIROmFiZeI%3D&reserved=0.

sgachau commented 5 years ago

Thank you for the clarification Regards

From: Dimitris Rizopoulos [mailto:notifications@github.com] Sent: Saturday, June 8, 2019 10:43 PM To: drizopoulos/JMbayes JMbayes@noreply.github.com Cc: Susan Gachau SGachau@kemri-wellcome.org; Comment comment@noreply.github.com Subject: Re: [drizopoulos/JMbayes] Multivariate LME (#27)

Yes, this is also a joint model.

From: sgachau notifications@github.com<mailto:notifications@github.com> Date: Friday, 07 Jun 2019, 12:24 PM To: drizopoulos/JMbayes JMbayes@noreply.github.com<mailto:JMbayes@noreply.github.com> Cc: D. Rizopoulos d.rizopoulos@erasmusmc.nl<mailto:d.rizopoulos@erasmusmc.nl>, Comment comment@noreply.github.com<mailto:comment@noreply.github.com> Subject: Re: [drizopoulos/JMbayes] Multivariate LME (#27)

Dear Prof. Rizopoulos,

Thank you for JMbayes package which is very helpful. I am fitting a model with four longitudinal outcomes and since i don't have a time-to-event outcome am using function mvglmer() function. I would like to know whether this qualifies as a joint model. I would also like to know whether shared parameter assumption hold for mvglmer().

Thank you Sgachau

— You are receiving this because you commented. Reply to this email directly, view it on GitHubhttps://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fdrizopoulos%2FJMbayes%2Fissues%2F27%3Femail_source%3Dnotifications%26email_token%3DADE7TTYVRNQNANNSBZEBLZTPZIZNDA5CNFSM4GPTRUO2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGODXFOEPI%23issuecomment-499835453&data=02%7C01%7Cd.rizopoulos%40erasmusmc.nl%7Cc4e5e0821eb3469af0af08d6eb324c84%7C526638ba6af34b0fa532a1a511f4ac80%7C0%7C0%7C636954998601837294&sdata=K4eVAX1N6jSOUwBS1CVtcFBdkL8pOlEqXkVboppI2Ys%3D&reserved=0, or mute the threadhttps://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-auth%2FADE7TT6SHGTLUNRISQ5OHL3PZIZNDANCNFSM4GPTRUOQ&data=02%7C01%7Cd.rizopoulos%40erasmusmc.nl%7Cc4e5e0821eb3469af0af08d6eb324c84%7C526638ba6af34b0fa532a1a511f4ac80%7C0%7C0%7C636954998601847306&sdata=pY26H7PhtVVvWO%2FyhsTaruU4mTIsP7KCGQIROmFiZeI%3D&reserved=0.

— You are receiving this because you commented. Reply to this email directly, view it on GitHubhttps://github.com/drizopoulos/JMbayes/issues/27?email_source=notifications&email_token=ABZU6TGTBUBODTD6USXYVX3PZQDS5A5CNFSM4GPTRUO2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGODXH4ITQ#issuecomment-500155470, or mute the threadhttps://github.com/notifications/unsubscribe-auth/ABZU6TCAWF4ZYCB7GT6PBXLPZQDS5ANCNFSM4GPTRUOQ.


This e-mail contains information which is confidential. It is intended only for the use of the named recipient. If you have received this e-mail in error, please let us know by replying to the sender, and immediately delete it from your system. Please note, that in these circumstances, the use, disclosure, distribution or copying of this information is strictly prohibited. KEMRI-Wellcome Trust Programme cannot accept any responsibility for the accuracy or completeness of this message as it has been transmitted over a public network. Although the Programme has taken reasonable precautions to ensure no viruses are present in emails, it cannot accept responsibility for any loss or damage arising from the use of the email or attachments. Any views expressed in this message are those of the individual sender, except where the sender specifically states them to be the views of KEMRI-Wellcome Trust Programme.