*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 at gmail.com/y.gelaw at uq.edu.au>* *"Change is good ... but it hurts "*
[R-meta] help
3 messages · Yalemzewod Gelaw, Michael Dewey, Viechtbauer Wolfgang (STAT)
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 at gmail.com/y.gelaw at uq.edu.au>* *"Change is good ... but it hurts "* [[alternative HTML version deleted]]
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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. Best, Wolfgang -----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 at gmail.com/y.gelaw at uq.edu.au>* *"Change is good ... but it hurts "*