Dear list & Matt,
After running a successful imputation in AmeliaView I wish to produce a
further few sets of (5) imputations and view the corresponding Diagnostics
for each set. I wish to do this without exiting & restarting AmeliaView.
If I do restart AmeliaView and run an (apparantly) identically specified set
of imputations on identical data I notice that for each set of imputations
the corresponding diagnostic plots vary slightly. I assume this is normal?
However after running a second and subsequent set of imputations the Output
log does not seem to change. Without restarting AmeliaView I change the
output directory before each fresh set of imputations; AmeliaView behaves
well, producing fresh sets of (5) imputations and saving them to the
allocated directory (csv files). However the log does not appear to change
and the diagnostic plots appear identical to those produced for the first
set of imputations. Am I missing something please?
many thanks
Simon UK
Dear Matt,
Thanks very much for that quick and helpful reply -- I had wondered
about doing what you suggested, but had thought perhaps I could 'cut
out the middleman' of the imputed datasets and pull the matrices
directly from Amelia. Clearly not, so now I know how to go forward.
Many thanks and best wishes
Chris
At 02:08 17/08/2015, Matt Blackwell wrote:
>Hi Chris,
>
>There is no way to get those covariance matrices from R directly,
>but you could calculate them from the imputed datasets and then
>average the quantities together using the Rubin rules to produce
>estimates of the covariance matrices and means. These imputed
>datasets are in the original scales, so this should produce what you
>are looking for.
>
>Cheers,
>Matt
>
>On Fri, Aug 14, 2015 at 4:39 AM Chris McManus
><<mailto:i.mcmanus@ucl.ac.uk>i.mcmanus(a)ucl.ac.uk> wrote:
>Hi -- I am new to this list, have tried searching for an answer on
>the existing posts, and don't think there is one already, but
>apologies if I have missed it.
>
>My primary interest is in the estimated means and covariances from
>the EM procedure (and bootstrapping helps as I need standard errors
>of means, covariances, etc). It is clear that covMatrices and mu are
>not on the original scale, and the JSS paper says on page 36 that
>"they refer to the variables after being transformed, centered and scaled".
>
>The question is therefore, How do it get them on the original scale?
>Is there a transformation matrix somewhere? Do I just alter the means
>and SDs back to the original raw values, or has there been a
>rotation of some sort as well? For my purposes I do need to know the
>values on the raw scale measures. I guess I am missing something
>here but am not sure what it is.
>
>Many thanks!
>
>Chris McManus
>University College London
>
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Hi -- I am new to this list, have tried searching for an answer on
the existing posts, and don't think there is one already, but
apologies if I have missed it.
My primary interest is in the estimated means and covariances from
the EM procedure (and bootstrapping helps as I need standard errors
of means, covariances, etc). It is clear that covMatrices and mu are
not on the original scale, and the JSS paper says on page 36 that
"they refer to the variables after being transformed, centered and scaled".
The question is therefore, How do it get them on the original scale?
Is there a transformation matrix somewhere? Do I just alter the means
and SDs back to the original raw values, or has there been a
rotation of some sort as well? For my purposes I do need to know the
values on the raw scale measures. I guess I am missing something
here but am not sure what it is.
Many thanks!
Chris McManus
University College London
