[R-meta] effect size calculation with a null standard deviation
Hi Marianne, I agree with Wolfgang that this is an unusual case and that figuring out how to handle it requires some contextual judgements, which folks on the mailing list aren't really in a position to advise on. That said, here are two avenues that you might like to investigate further: With only 3 observations in a given group, using a sample standard deviation to calculate a standardized mean difference for the group will give an EXTREMELY noisy estimate. Pooling the pre-test variance across groups (as in the Morris "dppc2" estimator) might mitigate the problem a bit--especially if only one of the groups is small and the other is larger. More broadly, the fact that you're encountering these sorts of situations makes me wonder whether it would be better to move to a different effect size metric, such as the response ratio (Hedges, L. V., Gurevitch, J., & Curtis, P. S. (1999). The meta?analysis of response ratios in experimental ecology. *Ecology*, *80*(4), 1150-1156.). This might be a good way to go if all of your outcomes are ratio scale measurements. My understanding is that this is pretty common in ecology. James On Thu, Feb 18, 2021 at 2:49 AM Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:
Dear Marianne, I suspect that you did not receive any responses, since what you are describing are really unusual cases which have not been discussed in the literature (as far as I know). I think you will just have to make a decision yourself how to handle these cases and be transparent about how you handled them. Best, Wolfgang
-----Original Message----- From: R-sig-meta-analysis [mailto:
r-sig-meta-analysis-bounces at r-project.org] On
Behalf Of Marianne DEBUE Sent: Thursday, 21 January, 2021 15:57 To: r-sig-meta-analysis at r-project.org Subject: [R-meta] effect size calculation with a null standard deviation Hi everyone, I'm conducting a meta-analysis in ecology. I'm using Morris "dpcc1"
formulas ( [
https://journals.sagepub.com/doi/10.1177/1094428106291059 | https://journals.sagepub.com/doi/10.1177/1094428106291059 ] ) to
calculate the
effect size and its variance. The effect size calculation implies a difference between post- and
pre-Mean which
is then divided by the pre-Standard deviation. I was wondering how to deal with studies which have pre-Standard
deviation = 0
(leading to a division by 0) ? How to deal with studies which have pre-Mean = post-Mean and a
pre-Standard
deviation = 0 (leading to 0 divided by 0) ? If pre-Mean = post-Mean , can
we
consider that the effect size is null, whatever the pre-Standard
deviation ?
The variance calculation implies a division by (N - 3) (N : sample size). How to deal with studies which have N = 3 ( leading to a division by 0) ? Thank you for your help, Marianne
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