At 13:17 10/04/2014, Julien Riou wrote:
>
> Message: 11
> Date: Wed, 09 Apr 2014 18:39:30 +0100
> From: Michael Dewey <i...@aghmed.fsnet.co.uk>
> To: Julien Riou <julien.rio...@gmail.com>, r-help@r-project.org
> Subject: Re: [R] Meta-analysis of prevalence at the country level with
> mgcv/gamm4
> Message-ID: <zen-1wxwtl-0005q4...@smarthost01a.mail.zen.net.uk>
> Content-Type: text/plain; charset="us-ascii"; format=flowed
>
Hi Michael,
Thank you for taking the time to help me.
So the first UK study with a median age of 25 is going to be used to
> estimate prevalence over a range of ages? You are going to have to
> make some very strong assumptions here which I personally would not
> want to make.
>
I'm a little confused by this. In my understanding, the mixed-effects model
does not do that. The slope of the relation between age and prevalence will
be estimated from the full pool of studies, and the country-level random
intercept will be estimated from all studies in the country. So the
assumption here is that the relation between age and incidence is the same
in every country, which is quite reasonable. Of course, there will be more
uncertainty with the estimation of the random intercept if there is few
studies in a country, or if there is a strong inter-study variance in a
country. This will influence the confidence interval of the random
intercept, and so the CI of the predicted prevalence for this country.
Your studies are ecological. You are estimating the relationship
between prevalence and being in a study of median age X which is not
necessarily the same as the relationship between prevalence and being
a person of age X.
Is there any possibility that in the real dataset you can fit your
> model to those studies which do provide age-specific prevalences and
> then use that to impute?
>
> You do not say when these studies were published but I would ask the
> authors of the primary studies if they can make the information
> available to you. You may have already done that of course. I referee
> quite a few papers on systematic reviews and my impression is that
> some authors are amenable to doing the work for you. You mileage may
> vary of course.
>
Yes, it would be easier to have prevalence for age subgroups of studies,
but we did not have access to that information for most studies even after
contacting the authors.
> >*Standard random-effect meta-analysis* with package meta.
> >
> >I used metaprop() to get a first estimate of the prevalence in each
> country
> >without taking age into account, and to obtain weights. As expected,
> >heterogeneity was very high, so I used weights from the random-effects
> >model.
>
> Which will be nearly equal and so hardly worth using in my opinion
> but again your mileage may vary.
>
The weights from the random-effects method were actually far from equals,
as sample size was highly variable between studies. With the RE method,
small studies have much more impact.
> I am afraid that is the way with systematic reviews, you can only
> synthesise what you find, not what you would like to have found.
> Anyone who has done a review will sympathise with you, not that that
> is any consolation.
>
I'm not sure I'm following your point. My objective is to synthesise the
included studies, while taking the age factor into account, since it is
strongly linked to prevalence and very heterogeneous. The alternative is to
only include studies with low median age, but I would lose a lot of
information.
Thank you again,
Julien
>
>
[[alternative HTML version deleted]]
Michael Dewey
i...@aghmed.fsnet.co.uk
http://www.aghmed.fsnet.co.uk/home.html
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