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Finalise the MvNormal model #88

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drbenvincent opened this issue Jul 23, 2016 · 3 comments
Open
1 of 4 tasks

Finalise the MvNormal model #88

drbenvincent opened this issue Jul 23, 2016 · 3 comments

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@drbenvincent
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drbenvincent commented Jul 23, 2016

(m,c) should be drawn from a multivariate normal distribution

  • finish JAGS model (for separate models)
  • think about reasonable priors

updated goals:

  • resolve error in mixed model first, before...
  • resolving error in fully hierarchical model. This may in fact automatically fixed if the mixed models get fixed.
drbenvincent pushed a commit that referenced this issue Jul 23, 2016
@drbenvincent drbenvincent changed the title Add new MvNormal model Finalise the MvNormal model Aug 7, 2016
@drbenvincent
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At this point we have...

Separate model: This works, and I'm happy with the setting up of the variance/covariance matrix. The resulting samples seem to be good.

Hierarchical model: This is NOT working, and is NOT a full hierarchical model. We are doing hierarchical inference on alpha and epsilon, but not on (m,c). We are in the middle of attempting to do hierarchical inference on r (correlation coefficient between m and c) but this is currently not working. Maybe we don't need to do this.

drbenvincent added a commit that referenced this issue Apr 6, 2018
@drbenvincent
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Hierarchical model Attempting to put hyper priors on m and c and just have one single r for all participants. But the model crashes. Not sure why

@drbenvincent
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So the MixedModel doesn't work either, so there is some other error than needs to be resolved here before addressing the fully hierarchical model.

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