[R-meta] Need to specify meta analysis weights
ruecker @end|ng |rom |mb|@un|-|re|burg@de
Fri Sep 4 12:54:59 CEST 2020
To your first question: First, Cochrane doesn't recommend weighting by
N. Cochrane (and others) recommend weighting by inverse variance, and in
the case of a binary outcome (you mention odds ratios) it is even better
to use a generalised linear mixed model (GLMM), e.g., logistic
regression. Also random effect models are available. A random effect
model is suitable to mitigate the effect of the largest study, or to
upweight smaller studies, which seems to be desired in your case.
To the second question: One possibility would be meta-regression with
length of follow-up as a covariate. Is length of follow-up a study-level
covariate, or an individual-level covariate? There is no problem in the
first case, but it may be problematic in the second case, when each
individual has a different length of follow-up.
Am 04.09.2020 um 12:22 schrieb Emanuele F. Osimo:
> Dear all,
> I am conducting a random-effects meta-analysis of 4 longitudinal studies
> measuring a blood inflammatory marker earlier on in life, and an unrelated
> outcome (measured in an interview) years later.
> The studies are not uniform in N (one is about 80k people, the 2 smallest
> are about 2k people) and in time to follow up (ranging from 8 to 21 years).
> I have odds ratios and 95% confidence intervals for the outcome based on
> cut-offs of the baseline marker (e.g. outcome for inflamed vs outcome for
> I have 2 questions for you:
> 1- if I use weighting by N, as recommended by Cochrane, I am basically
> reporting the findings of the larger study, which gets 88% of the weight.
> The larger study is possibly qualitatively less good than the 2 smallest
> studies. What do you suggest to use for weighting? Is there any compound
> weighting methods that takes into account, say, study quality, N and
> inverse variance?
> 2- time to follow-up: even if I am not measuring a difference in outcome
> over time, but just the risk of an outcome after an exposure, do I need to
> adjust for time to follow-up? And how?
> Many thanks in advance for your time and thoughts on this.
> Best wishes,
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Dr. rer. nat. Gerta Rücker, Dipl.-Math.
Institute of Medical Biometry and Statistics,
Faculty of Medicine and Medical Center - University of Freiburg
Stefan-Meier-Str. 26, D-79104 Freiburg, Germany
Mail: ruecker using imbi.uni-freiburg.de
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