Hi, Emilie.

For your second question. You may check Gleser and Olkin (2009). They gave
several formulas to estimate the sampling covariance for dependent effect
sizes. One of them can be applied in your case.

Gleser, L. J., & Olkin, I. (2009). Stochastically dependent effect sizes. In
H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research
synthesis and meta-analysis. (2nd ed., pp. 357-376). New York: Russell Sage
Foundation.

Regards,
Mike
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 Mike W.L. Cheung               Phone: (65) 6516-3702
 Department of Psychology       Fax:   (65) 6773-1843
 National University of Singapore
 http://courses.nus.edu.sg/course/psycwlm/internet/
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On Sat, Aug 20, 2011 at 10:19 PM, Michael Dewey <info@aghmed.fsnet.co.uk>wrote:

> At 16:21 17/08/2011, Emilie MAILLARD wrote:
>
>> Hello,
>> Â
>> I would like to do a meta-analysis with the package Â«Â metaforÂ Â».
>> Ideally I would like to use a mixed model because Iâ€™m interested to see
>> the effect of some moderators. But the data set I managed to collect from
>> literature presents two limits.
>> Â
>> -Â Â Â Â Â Â Â Â  Firstly, for each observation, I have means for a
>> treatment and for a control, but I donâ€™t always have corresponding
>> standard deviations (52 of a total of 93 observations donâ€™t have standard
>> deviations). Nevertheless I have the sample sizes for all observations so I
>> wonder if it was possible to weight observations by sample size in the
>> package Â«Â metaforÂ Â».
>> -Â Â Â Â Â Â Â Â  Secondly, some observations are probably not independent
>> as I have sometimes several relevant observations for a same design. More
>> precisely, for these cases, the control mean is identical but treatment
>> means varied. Ideally, I would not like to do a weighted average for these
>> non-independent observations because these observations represent levels of
>> a moderator. I know that the package Â«Â metaforÂ Â» is not designed for the
>> analysis of correlated outcomes. What are the dangers of using the package
>> even if observations are not really independent ? Â
>>
>
> Emilie,
> I am not sure whether this is the answer to your problem of observations
> which are not independent but you might also look at the metaSEM package
> http://courses.nus.edu.sg/**course/psycwlm/internet/**metaSEM/<http://courses.nus.edu.sg/course/psycwlm/internet/metaSEM/>
> I am still trying to understand his paper on this (see link for reference)
> but he is trying to embed meta-analysis within the structural equation
> framework and it may be possible to cope with lack of independence in that
> way. But as I say I am still trying to come to grips with the paper.
>
>
>  Â
>>
>> Thank you for your help,
>> Â
>> Ã‰milie.
>>        [[alternative HTML version deleted]]
>>
>
> Michael Dewey
> info@aghmed.fsnet.co.uk
> http://www.aghmed.fsnet.co.uk/**home.html<http://www.aghmed.fsnet.co.uk/home.html>
>
>
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