Many thanks to Philip, Tom and Paul for all of their
valuable help.
Best,
Ricardo
--- Steichen <[email protected]> wrote:
> Ricardo -
>
> A common assumption in meta-analysis of RR's is that
> log(RR) is
> approximately normally distributed (how good that
> assumption is never stated
> though). I would presume that the SE you have is,
> in fact, for log(RR),
> thus you have everything you need for a Z-test.
>
> Tom
>
> ----- Original Message -----
> From: "Ricardo Ovaldia" <[email protected]>
> To: <[email protected]>
> Sent: Thursday, March 11, 2004 7:48 PM
> Subject: Re: st: differences in relative risks
>
>
> > Thank you Philip. Unfortunately all I have is the
> RR
> > and the corresponding SE. I was thinking that some
> > method out of the Meta-analysis literature could
> be
> > used.
> >
> > --Ricardo.
> >
> > --- Philip Ryan <[email protected]>
> wrote:
> > > One way might be to write out two separate
> models
> > > (eg logistic or
> > > log-binomial, depending on your research design)
> and
> > > then use -suest- to
> > > test for equality of the coefficients of the
> > > suitably parameterised
> > > exposures. For example, as a very general case
> > > where both the exposures
> > > and the outcomes are different (and the sense is
> > > rather open to question!)
> > >
> > > is the RR for lung cancer among smokers (vs
> > > non-smokers) different from the
> > > RR of heart disease among males (vs females):
> > >
> > > glm lung smoker, link(log) fam(binomial)
> score(s1)
> > > est store A
> > > glm heart sex, link(log) fam(binomial) score(s2)
> > > est store B
> > > suest A B
> > > test [A_lung]smoker = [B_heart]sex
> > >
> > >
> > >
> > > Phil
> > >
> > >
> > >
> > > At 09:56 AM 11/03/2004 -0800, you wrote:
> > > >Dear all,
> > > >
> > > >Is there a way in Stata to compare if two
> relative
> > > >risks are equal, or alternatively if the ratio
> of
> > > two
> > > >relative risks (RRR) is equal to one?
> > > >
> > > >Thank you in advance,
> > > >Ricardo.
> > > >
> > > >__________________________________
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> > >
> > > Philip Ryan
> > > Associate Professor,
> > > Department of Public Health
> > > Associate Dean (Information Technology)
> > > Faculty of Health Sciences
> > > University of Adelaide 5005
> > > South Australia
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> > >
> >
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> >
> > =====
> > Ricardo Ovaldia, MS
> > Statistician
> > Oklahoma City, OK
> >
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