Hi Sarah, 

After taking a look, the behavior of Amelia with priors in 1.6.1 was buggy and should have looked like it does in 1.7. There was a bug in the R implementation of the priors that we (unintentionally) corrected when moving to C++. 

Note that for multiple overimputation, as you are doing, we should expect the overimputed variable to look roughly similar to the original variable, since each cell has its prior at its noisy observed value. This is why it does not look like the usual normal curve. 

Hope that helps!


On Tue, Mar 19, 2013 at 7:54 AM, Matt Blackwell <m.blackwell@rochester.edu> wrote:
Hi Sarah, 

It's tough to know exactly what's going on without the code used to generate the two plots. We reimplemented the main part of the EM algorithm in C++, but it should (roughly) produce the same results as before. If you post the simulation code, we'll definitely investigate. 

Cheers,
matt.

~~~~~~~~~~~
Matthew Blackwell
Assistant Professor of Political Science
University of Rochester


On Tue, Mar 19, 2013 at 4:52 AM, Sara Hogger <sara.hogger@gmx.de> wrote:
Dear all,

I have simulated non-normal data to check what Amelia ist doing when the assumption of multivariate normal distribution is not considerd. I generated a variable with two peaks as a mixture of two normal distributions.

In the density plot of Amelia 1.6.1 one can see that the overimputations are normal distributed anyway. That's what I expected because of the algorithm. In Amelia 1.7 the density of the overimputations are looking nearly exactly like the original variable with two peaks.

Can you explain to me what was changed in the algorithm?

To a better understanding I attached the density plots. The black lines are the simulated values, the red lines the values after overimputation.

Thanks a lot!
Sara


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