[R-meta] Metafor for Multivariate Analysis Questions - help please :)

[Ayesha Sadozai]

Hi All,

I hope this email finds you well. My name is Ayesha Sadozai and am a PhD student at the University of Sydney, Australia. I am reaching out as I am hoping to get more guidance/assistance for my PhD project for which I am hoping to use Metafor for. My research interest is in the area of paediatric neuropsychology. I am in the midst of conducting a meta-analysis.



My research looks at seven paediatric executive function domains (working memory, response inhibition, attention, set switching, etc.) across a range of neurodevelopmental disorders in 78 studies. These disorders include ADHD, Autism, Tourettes, FASD and Learning disorders. My data looks at executive function (EF) measures that load on the 7 areas and these measures have a varied quantitative quality i.e., for one study I may have 5 EF outcomes that are in milliseconds, reaction time and a general number out of 100. (I must add some papers have 12 to 20 executive function variables I have captured). These studies also have 1 control group and this control is compared to more than one neurodevelopmental disorder so for example I may have a study looking at EF domains in children with ADHD and ASD with typical controls.



I started off using escalc(measure="SMD"….etc) then used another function suggested by Wolfgang such as rma.mv(effectsize, var, etc… but am unsure how I organise the factors into my coding. Any suggestions?



In CMA, I can outline effect direction to conceptualise the direction the means are taking (lower numbers in some EF measure do not indicate a bad performance in some cases) – how can the metafor package account for this for my data? Is there a transform function that need to be written or if I use effect direction how do I incorporate it into my coding?



Apologies if my questions are simple, I am new to this world and attempting to learn it all during a lockdown. 😊

Kind Regards,
Ayesha Sadozai | PhD Candidate
Autism Clinic for Translational Research, Brain and Mind Centre
THE UNIVERSITY OF SYDNEY
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