NONMEM Users Network Archive

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Re: Missing value when modeling categorical data

From: wangx826
Date: 08 Oct 2009 15:50:17 -0500

Dear Nick,

I think I didn't make it clear in my first email that my model is a PK-PD
linked model, which means, the probability of a certain event is a function
of drug exposure which can describe as a function of time and some other
parameters like CL, V, etc. But it seems to me that the hazard function
only takes time into account. I am not familiar with survival analysis so
this might be a very basic question: How can I combine the PK/PD model with
the time-to-event model?

Thanks in advance,
Tianli

On Oct 8 2009, Nick Holford wrote:

>Tianli,
>
>Your data sounds like it could be described by a survival analysis. A
>time to event model will give you the survivor function i.e. the prob of
>not having had the event as a function of time. The event in your case
>is defined by the 'certain PD score'. The censoring will of course be
>taken care of by a typical survival analysis.
>
>Nick
>
>wangx826
>> 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 Thu Oct 08 2009 - 16:50:17 EDT

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