st: Re: case control design & analysis

[Mike Lacy <Michael.Lacy@colostate.edu>]

 Roger Webb wrote:


> Date: Wed, 2 Jul 2003 09:51:57 +0100
> From: "roger webb" <roger.webb@man.ac.uk>
> Subject: st: re. case control design & analysis
>
> Dear Statalist
>
> I have a case control study in which cases were inpatient suicides
> and eligible controls were alive and in inpatient care on the index
> date (i.e. the date of death of the corresponding case). There is no
> matching for age, sex, diagnosis, or any other explanatory variable.
>
> I'd greatly appreciate advice on the following two issues:
>
> 1) Is this a matched design, or does the single criterion for
> selection of controls (i.e. alive on index date) simply constitue
> sampling from the risk set (as in Clayton & Hills, 1993)? Therefore
> should I analyse the data using conditional logistic regression or
> just use the simple 'logit' / 'logistic' commands?

Yes, it is a matched design, with the matching factor being "in the risk 
set at time X."  I would analyze the data with both conditional and 
unconditional logit/logistic, and see if there is any difference in the 
results in terms of parameter estimates. If not, you could then just use 
the unconditional analysis. I have seen this strategy commonly pursued in 
published work, i.e. "We tried a conditional analysis and got the same 
results as the unconditional so we just relied on conditional." Perhaps 
someone can supply a citation justifying this approach.

Now, as for the followup question, as raised by another respondent to your 
question: What happens if you  use a conditional analysis on  a set of data 
for which there is no need to do so?  This issue was discussed a few years 
ago (2-5)  on the Epidemilogy list from U. Montreal.  What I thought was 
the definitive answer was a comment by the author of a paper with a simple 
proof indicating  that a matched analysis will *always* decrease estimation 
efficiency  unless the matching factor is actually a confounder. The 
archive of the Epi list is at 
http://www.listes.umontreal.ca/wws/arc/epidemio-l.
 The paper, who author was main a contributor to that discussion (and 
therefore possible a good search key in the Epi list archives) was:
Choi, B. G. K. 1984 "Unnecessary Stratification Pairing Can Never Increase 
Efficiency-- A Mathematical Proof."  International Journal of 
Epidemiology  13 (1): 116-117.

 When I looked this up in the Web of Science/Citation Index, I did see 
some demurring literature citing Choi, so one would want to follow up in 
that literature before taking him as the last word.

Regards,

Mike Lacy
Dept. of Sociology
Colorado State University


*
*   For searches and help try:
*   http://www.stata.com/support/faqs/res/findit.html
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/