Re: st: providing raw weights for multivariate meta-analysis

[Stas Kolenikov <skolenik@gmail.com>]

I personally think that -help weights- explains it all. Variance
weights are aweights: they state that the measurement error in a given
observation is such and such. The pweights are probability weights,
and when you invoke these, the calculation of not only the point
estimates, but also the standard errors is different (according to
probability sampling theory rather than the likelihood theory). There
are also frequency weights, which is essentially the result of
-collapse (count) ... , by(*)-. The iweights are "all other weights,
whichever these may mean for you" -- there is no strict definition,
and the program that allows them usually has its own idea what to do
with them.

Knowing very little about meta-analysis beyond the fancy name, I have
a feeling that you should be looking towards -gllamm- rather than
-xtmixed- to find the flexibility with the weights that you need. You
might still want to run (the much faster) -xtmixed- first to get good
starting values that you'd feed to -gllamm-. Joop Hox (a proper
reference is in place, according to the rules of Statalist; I have a
vague idea that this is a famous multilevel author) is a somewhat
opinionated guy, to my impression (although I am much more opinionated
than he is :)).

On Sun, Jul 10, 2011 at 7:02 AM, Nick Darson <nick.darson@googlemail.com> wrote:
> Dear Statalisters,
>
> I attempt to carry out a multivariate meta-analysis using "xtmixed". I
> have three outcome measures (the first level).
>
> When using a multilevel approach for the multivariate meta-analysis, I
> read that it is important to provide raw-weights (non-normalized) of
> the inverse sampling variances for the first level (containing the
> outcome measures).
>
> I know that HLM6 has a special function for this ("V-known") for two
> and three level models.
>
> Now, I wanted to know whether "pweights" is an equivalent solution for
> xtmixed in Stata?
>
> I must admit that I am a bit confused by the various descriptions of
> the weight functions I found online (aweights, iweights, etc - though
> this are not allowed for xtmixed) .
>
> Moreover, surprisingly,  I read in Hox (2010,p. 230) that public
> domain software for multilevel analysis does not support the required
> options for a multivariate model so far (i.e. providing raw weights
> and being able to constrain the lowest-level variance to 1 - however,
> both should be feasible).
>
> Thanks a lot for your support.
> Nick Darson
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-- 
Stas Kolenikov, also found at http://stas.kolenikov.name
Small print: I use this email account for mailing lists only.

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