> I thought about this some more, and I'm not sure that possibility is
> "to blame." In my time-dependent model, I don't think I'm doing
> anything different than is done for transplant in the Stanford
> Heart Study (the often used example for this kind of time-dependent
> covariate). As in my ca
From my experience, what you are seeing is almost certainly a patient
selection effect. (The number 1 reason for puzzling results is incorrect
coding
of a time-dependent covariate, but you appear to have been quite careful).
Assigning the implant as a non-time dependent covariate almost
On Tue, 2 Oct 2007, Kevin E. Thorpe wrote:
> Kevin E. Thorpe wrote:
>> Peter Dalgaard wrote:
>>> Kevin E. Thorpe wrote:
Dear List:
I have a data frame prepared in the couting process style for including
a binary time-dependent covariate. The first few rows look like this.
Kevin E. Thorpe wrote:
> Peter Dalgaard wrote:
>> Kevin E. Thorpe wrote:
>>> Dear List:
>>>
>>> I have a data frame prepared in the couting process style for including
>>> a binary time-dependent covariate. The first few rows look like this.
>>>
>>> PtNo StartEnd Status Imp
>>> 1 1
Peter Dalgaard wrote:
> Kevin E. Thorpe wrote:
>> Dear List:
>>
>> I have a data frame prepared in the couting process style for including
>> a binary time-dependent covariate. The first few rows look like this.
>>
>> PtNo StartEnd Status Imp
>> 1 1 0 608.0 0 0
>> 2 2
Kevin E. Thorpe wrote:
> Dear List:
>
> I have a data frame prepared in the couting process style for including
> a binary time-dependent covariate. The first few rows look like this.
>
> PtNo StartEnd Status Imp
> 1 1 0 608.0 0 0
> 2 2 0 513.0 0 0
> 3
Dear List:
I have a data frame prepared in the couting process style for including
a binary time-dependent covariate. The first few rows look like this.
PtNo StartEnd Status Imp
1 1 0 608.0 0 0
2 2 0 513.0 0 0
3 2 513 887.0 0 1
4 3
7 matches
Mail list logo
