[R] Multivariate Multilevel Model: is R the right software for this problem

[Bert Gunter]

Wrong list. Post to R-sig-mixed-models

-- Bert

On Thu, Apr 12, 2012 at 12:34 PM, Eiko Fried <torvon at gmail.com> wrote:
> Very interesting book!
> However, it doesn't cover multivariate models (I have 9 moderately
> correlated, categorical dependent variables).
>
> Again, I'm trying to find out whether 5 time-varying variables
> (dichotomous; five different life events "yes"/"no"; subjects can have
> several life events at the same time) cause differential profiles of my 9
> depression variables in a longitudinal sample, controlling for
> time-invariant covariates - exploratory.
>
> Is this possible in R? If so, how? I thought about multilevel multivariate
> mixed-effects models (random effect = subjects), but hardly find literature
> for R.
>
> Thanks a bunch!
> Eiko
>
>
>
> I recommend looking at chapter 6 of Paul Allison's *Fixed Effects
>> Regression Models*.  This chapter outlines how you can use a structural
>> equation modeling framework to estimate a multi-level model (a random
>> effects model).  This approach is slower than just using MLM software like
>> lmer() in the lme4 package, but has the advantage of being able to specify
>> correlations between errors across time, the ability to control for
>> time-invariant effects of time-invariant variables, and allows you to use
>> the missing data maximum likelihood that comes in structural equation
>> modeling packages.
>>
>> Hello,
>>
>> I've been trying to answer a problem I have had for some months now and
>> came across multivariate multilevel modeling. I know MPLUS and SPSS quite
>> well but these programs could not solve this specific difficulty.
>>
>> My problem:
>> 9 correlated dependent variables (medical symptoms; categorical, 0-3), 5
>> measurement points, 10 time-varying covariates (life events; dichotomous,
>> 0-1), N ~ 900. Up to 35% missing values on some variables, especially at
>> later measurement points.
>>
>> My exploratory question is whether there is an interaction effect between
>> life events and symptoms - and if so, what the effect is exactly. E.g. life
>> event 1 could lead to more symptoms A B D whereas life event 2 could lead
>> to more symptoms A C D and less symptoms E.
>>
>> My question is: would MMM in R be a viable option for this? If so, could
>> you recommend literature?
>>
>> Thank you
>> --T
>>
>>
>>
>
>        [[alternative HTML version deleted]]
>
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-- 

Bert Gunter
Genentech Nonclinical Biostatistics

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