[R-meta] Dealing with missing data in bivariate analysis

[Olina Ngwenya]

Thank you Wolfgang.

Regards

Olina

-----Original Message-----
From: Viechtbauer, Wolfgang (SP) <wolfgang.viechtbauer using maastrichtuniversity.nl> 
Sent: 28 March 2022 11:06
To: Olina Ngwenya <olina.ngwenya using manchester.ac.uk>; r-sig-meta-analysis using r-project.org
Subject: RE: Dealing with missing data in bivariate analysis

Dear Olina,

Depends a bit on what is missing. If values of predictor/moderator variables are missing, then one possibility is to use some kind of imputation technique. See, for example:

https://www.metafor-project.org/doku.php/tips:multiple_imputation_with_mice_and_metafor

Best,
Wolfgang

>-----Original Message-----
>From: R-sig-meta-analysis 
>[mailto:r-sig-meta-analysis-bounces using r-project.org] On Behalf Of Olina 
>Ngwenya
>Sent: Monday, 28 March, 2022 11:29
>To: r-sig-meta-analysis using r-project.org
>Subject: [R-meta] Dealing with missing data in bivariate analysis
>
>Dear R-sig-meta-analysts
>
>I have been doing bivariate meta-analysis using rma.mv(), but one of my 
>outcomes has missing values and I am getting this message "Rows with 
>NAs omitted from model fitting". My question is "Do we have other ways 
>of dealing with missing data in meta-analysis instead of discarding rows with missing values".
>
>Thank you
>
>Olina Ngwenya
>Research Assistant
>Centre for Biostatistics | School of Health Sciences | Faculty of 
>Biology, Medicine and Health | University of Manchester