Amelia February 2013

amelia@lists.gking.harvard.edu

9 participants
6 discussions

tscsPlot gives different values every time I run it

by Caterina Guinovart

Hi, I am trying to produce tscsPlots to compare the output of different Amelia models and every time I run the tscsPlot command on the same output I get a different graph (i.e. different values on the graph). Is this how it is supposed to be? In the Amelia vignette it says that the red points are the mean imputation for each of the missing values, but is this the mean of the 5 originally imputed values (if m=5), or is it the mean of the 100 imputations that tscsPlot runs? Any help will be much appreciated! Thanks, Caterina

11 years, 1 month

Progress Bar in Amelia

by Isaac Petersen

Is there any way to get a progress bar for the imputation progress in the command line version of Amelia? I'd like to be able to estimate how long the whole imputation process will take. For loops, one can use the following for a progress bar: pb <- txtProgressBar(min = 0, max = 999999, style = 3) for (i in 1:999999){ setTxtProgressBar(pb, i) } Is there an option to get a progress bar for a single or multiple imputations in the command line version of Amelia? Thanks!

11 years, 1 month

Amelia 1.7

by Matt Blackwell

Hi folks, James, Gary, and I are happy to announce Amelia 1.7 is up on CRAN for your enjoyment. You can install the update from the R prompt with the following line of code: install.packages("Amelia", repos = "http://cran.r-project.org") We have also updated the Windows installer at: http://gking.harvard.edu/amelia Amelia 1.7 brings a fairly large update to Amelia, which includes a complete rewrite of the Amelia internals to Rcpp. What does this mean for you? Much, much faster imputations (we have seen speedups of 10x on some examples). We have also added support for running Amelia in parallel using multiple cores in modern CPUs. You can find more about parallel in section 4.3 on page 16 of the Amelia manual: http://cran.r-project.org/web/packages/Amelia/vignettes/amelia.pdf Overall, this version should make imputations much faster. Other improvements and bugfixes: * Plots in AmeliaView should now use Quartz on Mac OS X instead of X11. * Amelia now requires R >=2.14.0. * Amelia now can run its imputations in parallel using infrastructure from R's parallel package. Note that R < 2.15.3 will crash if parallel is used while tcltk is loaded (or has been loaded and then unloaded). This will be fixed in R 2.15.3 (the patched version of 2.15.2) and we will require R>=2.15.3 when that version is released. * Fixed bug with character variables set to nominal. Please let us know if you run into any problems with this new version. Cheers, matt. ~~~~~~~~~~~ Matthew Blackwell Assistant Professor of Political Science University of Rochester url: http://www.mattblackwell.org

11 years, 1 month

Multicore with parallel option

by Ruben Arslan

Dear list, I installed 1.7 from source from the Cran repo to try out parallel imputation. Before 1.7 I did it with foreach mtfs_i <- foreach(i=1:5,.combine="ameliabind",.inorder=F) %dopar% { amelia(mtfs, m = 1, ) } and it worked fine. with 1.7 I tried using multicore using the parallel argument. mtfs_i <- amelia(mtfs, m = 1, parallel = "multicore", # note: this will crash R if tcltk is loaded prior to 2.15.3 ncpus = parallel::detectCores(), ) Both approaches finish without error, but I get a messed-up S3 object. So, in approach 1 using foreach ameliabind complains that it didn't get amelia objects. With approach 2 I get a list of Amelia objects, but the first two items are NULL and I don't get one list $imputations with many imputations, but a stitched-up object. Using this object with e.g. transform or overimpute fails, but doing the same with the third object in the list works (that's just one imputation then though). Regards, Ruben Arslan student assistant Lab: http://www.psychology.hu-berlin.de/profship/perdev Humboldt-University of Berlin Unter den Linden 6 10099 Berlin, Germany

11 years, 2 months

imputing count variable

by Alicia Doyle Lynch

I would like to impute a variable that counts the number of delinquent acts an individual engaged in in the last year. The variable will be used as an outcome and has a 0-inflated distribution so it will need to have all integer values if it is to be analyzed in a 0 inflated model. Does anyone have thoughts on whether it's better to 1. impute this variable as ordinal in order to obtain all integer values versus 2. impute as continuous and recode the values to integers after imputation? -- Alicia Doyle Lynch, Ph.D. Boston College, Lynch School of Education Department of Developmental and Educational Psychology Chestnut Hill, MA 02467 Phone: (617) 552-6437 e-mail: doylead(a)bc.edu

11 years, 2 months

Error of " resulting vector exceeds vector length limit in 'AnswerType'"

by OMER FARUK Orsun

Dear Lister, I am using Amelia II (Version 1.6.4) with a 500 GB computer specification and my data consist of directed dyads and my imputation model has 94 variables and 493,853 observations. I use the following command: library(Amelia) library(foreign) mydata <- read.dta("data.dta") require(Amelia) set.seed(1234) a.out <- amelia(mydata, m=10, p2s = 2, tolerance = 0.005, empri = .1*nrow(mydata), ts="year", cs="dyadid" , polytime=2, intercs = TRUE) After 7 hours, I receive the following message: amelia starting beginning prep functions *Error in cbind(deparse.level, ...) :* * resulting vector exceeds vector length limit in 'AnswerType'* I've already searched the Amelia II archieves and R archives, I was not able to locate a solution. I would deeply appreciate any help! Best Regards, Ömer _________________________________ Ömer Faruk Örsün PhD Candidate Department of International Relations Koç University CAS 289 _________________________________

11 years, 2 months

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Amelia February 2013