From: wangx826

Date: 07 Oct 2009 22:39:34 -0500

Dear NMUsers,

I am modeling ordered-categorical PD data versus time, but since the

clinical trial is ongoing, I don't currently have complete data set for

each subject. In other words, for some subjects, I have 1 year's PD data,

but for some others, I can only collect PD data for 1 month. For the 1

month's case, it is like missing data for the rest of time. But I need to

consider time course of the proportion of subjects who got a certain PD

score. In my case, if I use the general logistic regression model to fit

the relationship between time and proportions of event, would there be any

problem? If so, how can I avoid it? Or need I consider censoring like

survival analysis?

Any suggestion would be appreciated very much.

Thanks in advance,

Tianli

*****************************************************************

Tianli Wang

University of Minnesota

Received on Wed Oct 07 2009 - 23:39:34 EDT

Date: 07 Oct 2009 22:39:34 -0500

Dear NMUsers,

I am modeling ordered-categorical PD data versus time, but since the

clinical trial is ongoing, I don't currently have complete data set for

each subject. In other words, for some subjects, I have 1 year's PD data,

but for some others, I can only collect PD data for 1 month. For the 1

month's case, it is like missing data for the rest of time. But I need to

consider time course of the proportion of subjects who got a certain PD

score. In my case, if I use the general logistic regression model to fit

the relationship between time and proportions of event, would there be any

problem? If so, how can I avoid it? Or need I consider censoring like

survival analysis?

Any suggestion would be appreciated very much.

Thanks in advance,

Tianli

*****************************************************************

Tianli Wang

University of Minnesota

Received on Wed Oct 07 2009 - 23:39:34 EDT