[R-meta] Meta-analysis - missing study-specific variance

Mon, Aug 21, 2023 1:19 PM

In that case, you essentially want this (assuming that the dataset is called 'dat', the variable with the sample sizes 'ni', and the variable with the standardized regression coefficients 'beta'):

dat$id1 <- dat$id2 <- 1:nrow(dat)
V <- diag(1/dat$ni)
rownames(V) <- dat$id1

res <- rma.mv(beta, V=0, random = list(~ 1 | id1, ~ 1 | id2), R=list(id1=V), Rscale=FALSE, data=dat)
robust(res, cluster=id1)

The only paper I know of that, on a general/conceptual level, touches on this approach is:

Nakagawa, S., Noble, D. W. A., Lagisz, M., Spake, R., Viechtbauer, W., & Senior, A. M. (2023). A robust and readily implementable method for the meta-analysis of response ratios with and without missing standard deviations. Ecology Letters, 26(2), 232-244. https://doi.org/10.1111/ele.14144

but the context is quite a bit different. We also used a similar approach in:

Haslam, N., McGrath, M. J., Viechtbauer, W., & Kuppens, P. (2020). Dimensions over categories: A meta-analysis of taxometric research. Psychological Medicine, 50(9), 1418-1432. https://doi.org/10.1017/S003329172000183X

but again with a rather different context and the paper gives little details on this method. I also touched on this approach in this post:

https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2018-March/000731.html

I will have to leave it at that due to lack of time.

Best,
Wolfgang

-----Original Message-----
From: Angela Leanne Wilson [mailto:awils046 at uottawa.ca]
Sent: Monday, 21 August, 2023 21:41
To: Viechtbauer, Wolfgang (NP)
Cc: R Special Interest Group for Meta-Analysis; Angeline Tsui
Subject: Re: Meta-analysis - missing study-specific variance

Hello Wolfgang,

Thank you very much for this guidance. Unfortunately I do not have the entire
correlation matrices, and I only have the p-values for a small portion of
included studies. So it looks like Option 2 is the most viable choice.

Could you please direct me to which R package I would use (and/or any resources
to consult) in order to understand and perform this? I am new to using R and
meta-analysis, so any guidance you could provide would be incredibly helpful.

Many thanks,
Angela

On Aug 21, 2023, at 3:53 AM, Viechtbauer, Wolfgang (NP)

<wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:

Attention : courriel externe | external email

Dear Angela,

You would need the entire correlation matrix of all variables involved in a

regression model to compute the sampling variance of a standardized regression
coefficient of such a model. I assume that this is not available to you.

I see a few alternative options:

1) Do you have the p-values corresponding to these regression coefficients? If

so, you could use this to compute the partial correlation coefficients and
conduct the meta-analysis using those. See:

https://wviechtb.github.io/metafor/reference/escalc.html#partial-and-semi-

partial-correlations

2) You could fit a model that assumes that the sampling variances of the

standardized regression coefficients are inversely proportional to the sample
sizes and then use robust inference methods. Making this work isn't entirely
straightforward, so I wouldn't suggest to consider this approach unless 1) is not
an option.

Best,
Wolfgang

-----Original Message-----
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org]

On

Behalf Of Angela Leanne Wilson via R-sig-meta-analysis
Sent: Monday, 21 August, 2023 4:11
To: r-sig-meta-analysis at r-project.org
Cc: Angela Leanne Wilson
Subject: [R-meta] Meta-analysis - missing study-specific variance

Hello all,

I am conducting a meta-analysis to summarize effect sizes from different

studies

that ran mediation analysis.

I have extracted the standardized regression coefficients (i.e., the indirect
effects from each mediation study) as the effect size. I also have the sample
size for each study, however I found that only a few studies reported any
error/variance estimate (probably because the authors have reported a
standardized regression coefficient and thus they did not report any
error/variance of the corresponding regression coefficient). In this case, it
means that many studies in my meta-analysis lack study-specific variance
information.

My understanding is that the study-specific variance is needed to calculate

the

weight for each study when calculating the average effect size across studies.
May I ask if you can suggest what I need to do to estimate the study-specific
variance?

(Apologies I do not have any code as I cannot begin the analysis without first
resolving this issue)

Many thanks,
Angela

Angela Wilson (she, her/elle)
Doctoral Candidate, Clinical Psychology
University of Ottawa
Healthy Active Living and Obesity (HALO) Research Group
Children?s Hospital of Eastern Ontario (CHEO), Research Institute
Email: awils046 at uottawa.ca

[R-meta] Meta-analysis - missing study-specific variance

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