I am trying to load SPSS datasets into AmeliaView. I started with small
datasets that include just a handful of variables (5-7) to see how the program
works. But everytime I load the datasets and 'Summarize Data', AmeliaView
tells me that all the observations are missing for the variables, which is
definitely not true in the original dataset.
What am I doing wrong?
Thank you,
-Rahsaan
Rahsaan Maxwell, Ph.D.
Assistant Professor
Department of Political Science
University of Massachusetts, Amherst
Postdoctoral Fellow
Transatlantic Academy
German Marshall Fund of the United States
http://rahsaanmaxwell.googlepages.com
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Hello,
How does one run diagnostics based on saved output from an imputation
process (if indeed it is possible)? If the imputation takes a long time
and it is not possible to do the diagnostics immediately, can one shut
down R and return to the diagnostics later?
For example, if one does an imputation of the following sort:
>output=amelia(data=data,m=5,archive=TRUE,outname="imputed",write.out=TRUE,keep.data=TRUE)
And then saves the output as follows:
>save(output,file="out.rData")
And then shuts down R to return at a later date to the diagnostics, how
would you go about completing the following command line:
>overimpute(data=data,output=????,var=5)
I guess this is in some sense a question about how to read in an
".rData" data frame properly.
Thank you in advance,
Steve Shewfelt
PhD Candidate
Department of Political Science
Yale University
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Apologies - one additional question:
Is it possible to ensure the label of the variable being overimputed is
included in the graph produced by "overimpute"? When I run
"compare.density", each graph produced is labeled, but the same is not
the case for overimpute. Is there a way to make this happen?
Thanks again,
Steve Shewfelt
PhD Candidate
Department of Political Science
Yale University
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I could use some assistance in using AmeliaView. I have data from a clinical trial where 57 participants were randomized to one of two treatments. I am currently looking at data from measurements taken at three time points – pretreatment, midtreatment, and posttreatment and would like to impute missing values from those who dropped out or failed to complete assessments (i.e., non-random, non-ignorable missing data). The input data format is SPSS. I have been getting a range of error messages, but I think they stem from not organizing the data file correctly. Below is a partial illustration of the current organization in SPSS (Dep=score on a depression measure, Neg=score on a measure of negative thinking), which does not work:
Participant Treatment Dep-pre Dep-mid Dep-post Neg-pre Neg-mid Neg-post
1 1 28 20 15 80 65 50
2 2 25 23 20 85 80 80
3 1 30 25 80 70
4 2 20 70
.
.
.
Any thoughts on creating a data frame the corresponds to the elements in Amelia View’s _Variables Dialog_ and _Time Series Cross Sectional Dialog_ options would be much appreciated.
Sincerely,
Scott
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