R help - May 2011 - two-way group mean prediction in survreg with three factors

I'm fitting a regression model for censored data with three categorical
predictors, say A, B, C.  My final model based on the survreg function is 

Surv(..) ~ A*(B+C).

I know the three-way group mean estimates can be computed using the predict
function. But is there any way to obtain two-way group mean estimates, say
estimated group mean for (A1, B1)-group?  The sample group means don't
incorporate censoring and thus may not be appropriate here.

 

Pang Du

Virginia Tech


	[[alternative HTML version deleted]]

I hope not!

Facetiousness aside, the model that you have fit contains C, and,
indeed, an interaction between A and C.  So, the effect of A upon the
response variable depends on the level of C.  The summary you want
must marginalize C somehow, probably by a weighted or unweighted
average across its levels.  What does that summary really mean?  Can
you meaningfully average across the levels of a predictor that is
included in the model as a main and an interaction term?

Best wishes

Andrew

On Wed, May 04, 2011 at 12:24:50PM -0400, Pang Du wrote:
> I'm fitting a regression model for censored data with three categorical
> predictors, say A, B, C.  My final model based on the survreg function is 
> 
> Surv(..) ~ A*(B+C).
> 
> I know the three-way group mean estimates can be computed using the predict
> function. But is there any way to obtain two-way group mean estimates, say
> estimated group mean for (A1, B1)-group?  The sample group means don't
> incorporate censoring and thus may not be appropriate here.
> 
>  
> 
> Pang Du
> 
> Virginia Tech
> 
> 
> 	[[alternative HTML version deleted]]
> 
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-- 
Andrew Robinson  
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