Jay Kaufman wrote (excerpted):
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Stata appears to have no built-in functions for matched COHORT data (as
opposed to matched case-control data) but the relevant formulas ar shown in
Rothman & Greenland "Modern Epidemiology 2nd Edition, p. 283 (i.e. for the
Mantel-Haenszel RR instead of M-H OR as provided in Stata's -mhodds-
command).
However, the M-H RR is equal to the crude RR exactly because matching in a
COHORT study (as opposed to a case-control study) adjusts for confounding by
the matching factor. See discussion in R & G 1998 pp. 283-285.
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In lieu of a Mantel-Haenszel command for risk ratio in Stata, I suppose that
you could try something like -gllamm/xtgee , i(pair) family(binomial)
link(log) eform- in a pinch, but is there a reason to prefer risk ratios
over odds ratios? Is it for ease of interpretation? I don't have Rothman
and Greenland's text, but it seems from Jay's post that they abide by the
convention of odds ratios for case-control studies, risk ratios for cohort
studies. Does that represent universal thinking among experts currently for
analysis and reporting of cohort studies with a binomial outcome? I just
was under the impression that odds ratios were a more "natural" metric for
this kind of data regardless of whether from a case-control or cohort
design.
Joseph Coveney
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