[R-sig-ME] need help with mixed effects model

[MHH Stevens]

Hi Nick,
You might want to look at the sem package.
Hank
On Mar 5, 2008, at 6:02 AM, Nick Isaac wrote:

> You can do SEM-type models using the smatr package. Only drawback  
> is that
> you'd have to treat Rat as a fixed effect. This is a general class of
> problem that afflicts several of my current projects, and I'm  
> having a tough
> time choosing between mixed effect and structural equation models. The
> former is most appropriate for partitioning the variance, but the  
> latter is
> most appropriate for modelling error variance in the observations.  
> I don't
> see an obvious solution with the available tools and would  
> appreciate any
> general insights.
>
> Cheers, Nick
>
>
> On 04/03/2008, Ken Beath <kjbeath at kagi.com> wrote:
>>
>> The concern that Doug had is I assume that gene1 and gene2 are both
>> measured with error, and this type of model assumes that the
>> covariates are measured without error or for practical purposes much
>> lower than the error in the dependent variable. Ignoring this problem
>> biases the coefficients towards zero with consequent loss of power. I
>> don't have any idea how important this is, it all depends on the  
>> error
>> of your measurements. The usual solution is structural equation
>> modelling (SEM). This is something I haven't tried, so I have no idea
>> how easy or how well it will work.
>>
>>
>
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>
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Dr. Hank Stevens, Assistant Professor
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