OT - study design advice sought

Hi Neil

From a medical angle I would see the occurrence during one's lifetime of
cardiovascular disease (CVD) is being used as a marker for some
underlying increased risk of CVD and it is this hidden risk variable(s)
that is being 'linked' to AMD.
If an underlying increased risk variable is being postulated perhaps
rather than using lifetime CVD events as the surrogate marker only
'premature' CVD should be the criterion.
As for the method of statistical analysis I can have no formal informed
comment (not being a statistician) but I imagine a regression technique
using premature CVD events as independent variables and AMD as dependent
variable (? With Logistic regression methods) could be discussed.
Of interest in terms of data dredging is factor analysis (do throw
things yet) as an exploritory method just using default methods and
varimax rotation to see if CVD and AMD load on the same factor and what
else they load with. I've seen some interesting but soft outcomes of
this type on analysis when applied to multivatiate medical numerical
result data sets.
Regards
Nigel (Pathologist)

Neil,

It is not entirely clear how your matching was done.

Are the controls matched to  cases at the date of AMD diagnosis (which I
realize must be a pretty soft thing). And how was the data collection
done --- around the time of diagnosis?

Or was the study done a long time after AMD diagnosis (for some).

As you describe it, the latter seems to be the case, i.e. you have
matched prevalent cases of AMD to prevalent persons in the population.
In that case what you get out of you study would be PREVALENCE
odds-ratios associated with various risk factors. In that case it makes
perfectly sense to have variables that are subsequent to disease. The
prevalences you will be addressing are namely a function both of the
disease incidence related to factors prior to disease and to survival
related to factors subsequent to disease.

The former sampling scheme (incidence-density sampling) would give you
odds-ratios that were interpretable as hazard rates, and of course
variables referring to time after diagnosis would not make any sense.
But by the mere nature of the sampling scheme they would not be there
anyway, since sampling was AT time of diagnosis.