Hello
I am analyzing a matched subjects case control study where some strata have one case with multiple controls and other strata have multiple cases and multiple controls. I have read that COX Regression would work for single case strata but not so well for strata with more than one case because the method used on COX Reg for handling tied survival times, Breslow's method, will not produce accurate results... My question is, is there some technique that can be implemented that can handle this type of design within SPSS? Any help is greatly appreciated. Thanks Rob ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
Cox easily
handles {case, control} = {1,1}, {1,n}
{m,n} can perhaps
be broken into m*{1,n}
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Administrator
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Alternatively, one could use generalized estimating equations (GEE) to account for the correlated nature of the data. See the GENLIN procedure. (IIRC, I used both conditional logistic regression and GEE with 1:3 matching, and found that the results were very similar.) For an introduction to GEE, see the article by James Hanley et al. in Am J Epidemiol 2003;157:364–375.
HTH.
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In reply to this post by MaxJasper
Thanks for the thoughts on how to best deal with this. Question - maxjasper indicated "Cox easily handles {case, control} = {1,1}, {1,n} {m,n} can perhaps be broken into m*{1,n}". Have you tried this approach? Would this approach require the computation of additonal variables? Sorry for my ignorance but this is a relatively new area for me.
rob |
{case, control} =
{1,1} and {1,n} can easily be implemented using Cox...However, {m,n} data I
break them into m*{1,n} but here is an advice by Marija
Norusis:
Max.
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