Hi, perhaps I'm doing something wrong, but ask=FALSE doesn't seem to
stop the ask in plot.amelia. Example call:
png(file =
paste("/home/james/repos/bdp/doc/images/",fname,"_a_withbounds_%03d.png",sep=""),
width=1200, height=850, bg="transparent")
plot(df.amelia,ask=FALSE)
dev.off()
I always see:
Hit <Return> to see next plot:
Regards,
James Marca
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Hi Matt, I am having trouble implementing Amelia in a dataset of 50,000
observations and ~200 variables.
After running the code:
*a.out1 <- amelia(dataHIV, m = 5, noms = c("v000", "v001", "v003", "v004",
"v006",*
* ** **"v014", "v016", "v101", "v102", "v116", "v113", "v119", "v120",*
* ** **"v121", "v122", "v123", "v124", "v125", "v127", "v128", "v129", *
* **"religion", "currentmaritalshort", "morethanoneunion", "region", *
* **"cluster", "v103", "ethny", "radioteleall", "transportall", "country"),
*
* **ords = c("v013", "v106", "v105"), idvars = c("caseid", "idnumber",
"hivid",*
* ** "hcaseid", "acaseid"))*
I get the output:
*Error in if (sum(non.vary == 0)) { : *
* argument is not interpretable as logical*
*In addition: Warning message:*
*In FUN(X[[4L]], ...) : NAs introduced by coercion*
I implemented the suggestion made in post below -- I have downloaded and am
using the most recent Amelia II version -- but am still unable to run the
program, even when I trim the dataset down to a small number of variables,
and delete out invariant variables. I also get warnings that some nominal
variables have many categories, but assume this is unrelated
http://lists.gking.harvard.edu/lists/amelia_at_lists_gking_harvard_edu/2010…
Do you have any suggestions?
Thanks for your help - Nick
--
Nick Menzies
nick.menzies(a)gmail.com
404 217 1076
--
Nick Menzies
nick.menzies(a)gmail.com
404 217 1076
In the Honaker and King 2010 article linked from the Amelia home page
there is a reference to using spatial proximity in an analysis:
We use the same technology for putting priors on individual
missing cell values to borrow strength from information in the data
of neighboring or similar countries via user-specified proximity
matrices.
I can't find any details in the appendix of the paper, nor can I find
any mention of how to do such a thing in the Amelia docs. Is this an
undocumented feature, or is it something that must be done outside of
Amelia when developing multiple priors. If it is the latter case,
I've got no clue how to do that and so would appreciate some pointers.
Regards,
James Marca
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Hi,
I am trying to impute my data file that has participants over three days of
sampling and two predictors. I set up my data in SPSS with like this:
ID Time predictor1 predictor2 measure 1 measure 2 measure 3 measure
4
101.0 1.0 10.0 8:58 1.097 -0.492
9.680 -0.095
101.0 2.0 10.0 9:00 2.399 0.299
13.202 -0.801
101.0 3.0 10.0 8:15 1.636 -0.316
20.445 -0.931
102.0 1.0 27.0 7:07 3.903 0.473
31.106 -0.916
102.0 2.0 27.0 7:21 3.797 0.473
31.994 -0.966
102.0 3.0 27.0 7:34 2.829 0.227
29.497 -0.958
I tried using the time series cross sectional option using time as ts and ID
as cs. I put the polynomials time as 1 (although I'm really not sure about
that) and used an EM prior of 4. At the bottom of my AmeliaView it says I
have 381 observations and 9 variables, which does not exceed the p(p+3)/2
formula yet I am still getting error code 34:
Amelia Error Code: 34
The number of observations in too low to estimate the number of
parameters. You can either remove some variables, reduce
the order of the time polynomial, or increase the empirical prior.
You have recieved an error. You can close this window and reset
various options to correct the error.
I'm not sure what I'm doing wrong! Any help would be greatly appreciated!
Thank you,
Sivan
