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>> Original Message
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Original Message
> From: Angelo Franchini [mailto:angelo.franch...@bristol.ac.uk]
> Sent: Wednesday, August 04, 2010 16:26
> To: Viechtbauer Wolfgang (STAT)
> Cc: 'Angelo Franchini'; r-help@r-project.org
> Subject: RE: [R] metafor and meta-analysis at arm-level
>
010 16:26
To: Viechtbauer Wolfgang (STAT)
Cc: 'Angelo Franchini'; r-help@r-project.org
Subject: RE: [R] metafor and meta-analysis at arm-level
> Hello Wolfgang.
>
> I'd appreciate if you could help me check whether I am doing the proper
> thing to do an arm-level meta-an
Room B2.01 (second floor)
6200 MD Maastricht, The Netherlands Debyeplein 1 (Randwyck)
>
>
> Original Message
> From: r-help-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of Angelo Franchini
Sent: Tuesday, July 06, 2010 10:37 To: Wo
day, July 06, 2010 10:37 To: Wolfgang Viechtbauer
Cc: r-help@r-project.org; Angelo Franchini
Subject: Re: [R] metafor and meta-analysis at arm-level
> Hello Wolfgang,
>
> Thank you very much for your response.
> When you mentionthe "appropriate design matrix", do you mean
Hello Wolfgang,
Thank you very much for your response.
When you mentionthe "appropriate design matrix", do you mean by that the
'n1i, n2i, m1i, m2i, sd1i, sd2i' arguments of the rma function, or am I
missing something?
I read the documentation on metafor (introduction), rma/rma.uni and
escalc, and
Hello Angelo,
You can either supply the arm-level outcomes and corresponding sampling
variances directly (via the yi and vi arguments) or supply the necessary
information so that the escalc() or rma() functions can calculate an
appropriate arm-level outcome (such as the log odds). See the docum
Hi,
I have been looking for an R package which allowed to do meta-analysis
(both pairwise and network/mixed-treatment) at arm-level rather than at
trial-level, the latter being the common way in which meta-analysis is
done.
By arm-level meta-analysis I mean one that accounts for data provided at
t
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