[R-meta] help

Viechtbauer Wolfgang (SP) wolfgang.viechtbauer at maastrichtuniversity.nl
Thu Oct 19 10:34:55 CEST 2017

In terms of using methods such as multiple imputation, these articles are also relevant:

Ellington, E. H., Bastille-Rousseau, G., Austin, C., Landolt, K. N., Pond, B. A., Rees, E. E., . . . Murray, D. L. (2015). Using multiple imputation to estimate missing data in meta-regression. Methods in Ecology and Evolution, 6(2), 153-163. doi:10.1111/2041-210x.12322

Pigott, T. D. (2001). Missing predictors in models of effect size. Evaluation and the Health Professions, 24(3), 277-307.


-----Original Message-----
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org] On Behalf Of Michael Dewey
Sent: Wednesday, 18 October, 2017 13:09
To: Yalemzewod Gelaw; r-sig-meta-analysis at r-project.org
Subject: Re: [R-meta] help

You could assume some distribution of ages between the lower and upper 
limit and then calculate its mean.

Note though that what you propose is an ecological analysis - you are 
not looking at the effect of age but at the effect of being enrolled in 
a study with people of a certain average age.

On 18/10/2017 09:51, Yalemzewod Gelaw wrote:
> *Does missing of mean age dealt for Meta-analysis in r? *
> Hi everyone,
> I am doing a meta-analysis for single proportion.
> During my review I found some articles that didn’t present the mean age of
> the study participants, some of them reported the age group. I want to do a
> moderator analysis (meta-regression) to find out the source of
> heterogeneity. I am asking your experience whether it’s possible to handle
> the missing mean age using missing data handling techniques.
> To give you some information about the data: 22 out of 69 included articles
> didn't report the mean age.
> If I am not burden you with this, please provide me supportive documents.
> Thank you for any help!
> *Sincerely, *
> *Yalemzewod Assefa Gelaw  (Yalem)*
> *PhD Candidate, the University of Queensland, Australia *
> *Email: yalassefa at gmail.com <http://yalassefa@gmail.com/y.gelaw@uq.edu.au>*
> *"Change is good ... but it hurts "*

More information about the R-sig-meta-analysis mailing list