[R-meta] Comparing effect sizes in multivariate meta analysis

McCutcheon, Robert robert@mccutcheon @ending from kcl@@c@uk
Tue Oct 30 17:14:01 CET 2018

Dear All,

I have data from a number of randomised placebo controlled trials, each trial reports data on the effect  of the drug on both ‘positive’ and ‘negative’ symptoms. I wish to determine whether the drug has a greater effect on negative or positive symptoms

As I do not know the within-study correlations I have estimated a covariance matrix using the ClubSandwich package, and intend to run the analysis with a range of values for ‘r’:

Vlist <- impute_covariance_matrix(vi = multistudy[[6]]$vi, cluster = mydata_multi$studyid, r=0.5 )

I then conduct the multivariate analysis as follows:

MultiMeta <- rma.mv(yi = yi, V = Vlist, mods = ~factor(posneg)-1, random = ~factor(posneg)|studyid, struct = "CS", data = mydata_multi)

Where yi is the calculated effect size, ‘posneg’ is the label describing whether the results of that row refers to positive or negative symptoms, and ‘studyid’  is a separate label for each study.

This gives me separate effect sizes for positive and negative symptoms but I wonder if anyone could advise how I test whether these effect sizes are significantly different form one another, i.e. whether the drug has a greater effect on positive as compared to negative symptoms?

Many thanks for your time,


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