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Re: st: gllamm and mim output for multi-level model

From   Christian Villenas <[email protected]>
To   [email protected]
Subject   Re: st: gllamm and mim output for multi-level model
Date   Mon, 18 Oct 2010 09:34:45 -0400

Thanks so much for your response. I guess for me the confusion still
lies in the output. If it's a matter of learning Cholesky
decomposition, why does the gllamm output (without mim) provide the
variances/covariances? Are you saying that I need to learn Cholesky
decomposition in order to somehow aggregate the imputed data to get
the  level 1 and 2 variance/covariances?



On Fri, Oct 15, 2010 at 3:12 PM, Stas Kolenikov <[email protected]> wrote:
> On Fri, Oct 15, 2010 at 12:57 PM, Christian Villenas
> <[email protected]> wrote:
>> I am working on a project that uses both gllamm and mim commands. When
>> running my models, I notice that the level 1 and 2
>> variance/covariances, as well as random effects are missing from the
>> output. Instead I get coefficients for the level 2 identifier and
>> random effects. What do those coefficients mean, and can I use them to
>> obtain the variance/covariance as per the gllamm output without the
>> mim command?
> You'd need to learn the internal parametrization used by -gllamm-.
> Level 2 is parametrized via Cholesky decomposition, so the variances
> and covariances are not directly available.
> --
> Stas Kolenikov, also found at
> Small print: I use this email account for mailing lists only.
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