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List:       r-sig-mixed-models
Subject:    Re: [R-sig-ME] Effect sizes for mixed-effects models
From:       Schäfer, L. (Lena) <l.schafer () student ! ru ! nl>
Date:       2019-10-11 16:01:30
Message-ID: 470E0E7B-86B8-4DA6-803A-AB3B045B00A1 () student ! ru ! nl
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Hi David,

Thank you for your response! We have the raw data for some studies but only info on \
the sample/cluster size, the lme4 output and the respective ICC for other studies. \
Since we are conducting a meta-analysis, we cannot get access to all data-sets (eg., \
problems with data protection, unpublished data-sets). However, using the info on the \
sample and cluster size and the ICC, we can derive the effective sample size (Aarts, \
Verhage, Veenvliet, Dolan, & van der Sluis, 2014) related to the study.

I am not sure what you are referring to with *lower bound for the effective sample \
size*. Is this value calculated using another formula or is it essentially equal to \
the number of participants (as suggested by Phillip Alday)?

Thank you for a clarification!

Best,
Lena



Am 10.10.2019 um 19:34 schrieb David Duffy \
<David.Duffy@qimrberghofer.edu.au<mailto:David.Duffy@qimrberghofer.edu.au>>:


we want to derive the variance related to Cohen's d for a mixed-subjects design with \
some participant conducting a task only in the control condition and other \
participants conducting the task in the control and in the experimental condition \
(within-subjects design).

[...] we only have access to parts of the raw data-sets

Do you have the raw data or appropriate summary statistics from this mixed-subjects \
study? Could you get it? I think the "usual" approach would be to use a conservative \
lower bound for the effective sample size.

Cheers, David Duffy.


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