Amelia May 2012

amelia@lists.gking.harvard.edu

4 participants
5 discussions

by Ringelhan, Stefanie

Hi, I'm rather new to Amelia and have some troubles with it. Thus I would be very happy, if you could give me a hint. Here are my problems I'm dealing with: I have two warning messages coming up when I try to run the imputation command on Amelia (using R) and I don't know how to handle them: · "You have a small number of observations, relative to the number, of variables in the imputation model. Consider removing some variables, or reducing the order of time polynomials to reduce the number of parameters." è What would be a good relation of observations to variables? Right now I have 292 observations and 121 variables in the data file. And I do not want to delete more variables, as they are pretty much the fundamental variables I want to do calculations with. · "The resulting variance matrix was not invertible. Please check your data for highly collinear variables." è Is Amelia not running properly in the case of collinear variables? Do I have to delete highly correlating variables or is there a way to work around? There are some variables that are very likely to correlate with each other, however I do not want to delete them from the sample as they will be important in further analysis. Furthermore Amelia imputated 5 times, however data was only printed out in the last one of 5 excel sheets (using the command: write.amelia(obj=a.out, file.stem = "outdata", format = "csv")). Do you have any idea why there is only data written to the last excel sheet? Or is this already the merged data sheet from all 5 imputations? Cheers, Stefanie Follow us on Facebook: www.facebook.com/TUM.LSO<https://xmail.mwn.de/owa/redir.aspx?C=4f6285cd2ca7472e93498471917db3d0&URL=…> __________________________________ Dipl.-Psych. Stefanie Ringelhan Lehrstuhl für Strategie und Organisation Prof. Dr. Isabell M. Welpe Fakultät für Wirtschaftswissenschaften Technische Universität München Leopoldstrasse 139 D-80804 München (Germany) Tel.: +49-(0)89-289-24824 Email: s.ringelhan@<mailto:m.mustermann@>tum.de http://www.strategie.wi.tum.de<https://xmail.mwn.de/owa/redir.aspx?C=4f6285cd2ca7472e93498471917db3d0&URL=…>

11 years, 10 months

cannot install AmeliaViewer under Win 7 (64 bit) with R ver2.15.0

by Cristina Grama

Hello all, I cannot install AmeliaViewer because it doesn't recognize my R folder. I work under Windows 7, 64 bit, and I have R installed in: C:\Program Files\R\R-2.15.0 When prompted by the wizard, I have selected this folder, to no avail: "R directory is incorrect" I have tried also the subfolders \bin and \bin\x64, just to eliminate all possibilities, but I get the same error message. What could be the problem here? Thank you! --Cristina.

11 years, 10 months

Your expertise

by Nurjamal Omurkanova

Dear Amelia developers, Because of the big number of missings in my dataset and since I further plan evaluation of counterfactuals, I wanted to use Amelia software. In my study I am exploring the relationship between oil income and corruption. I use corruption data from the ICRG dataset. This data ranges from 0 to 6. However, I have to mention that there are many in-between values (92 unique values in the current version of my dataset). Nevertheless, since most of the observations fell into a limited number of categories I feel obliged to use an ordered logit model. For the statistical analysis with ordered logit model I have rounded original corruption data. In my dataset I have 3640 observations and 117 variables. This is a panel data with 167 countries for 23 years. As I tried to import my data into Amelia there were several error messages and imputation process was broken. I therefore dropped all “unnecessary” variables. By now there are 21 variables left in the dataset. (1) For Amelia imputations I employed “raw” corruption data, i.e. without rounding it beforehand. At the same time, I tried to declare corruption as ordinal data. As a result, there was an error message in Amelia output. I therefore imported corruption data into Amelia as a continuous one. The imputation output has shown that now this corruption data ranges from [-.99700195 to 8.0574379]. I am afraid that I cannot use this data for my analysis because it varies from the original corruption data range. Would you recommend me that I round corruption data before I begin with Amelia imputations? (2) My main independent variable is oil income per capita. I took log of oil income before imputation. As result of this transformation, the number of missing values increased from 54 to 1663 (mainly because of the zero values for oil income). Imputation ran successfully and there are no missing values in the dataset. However, data was imputed for non-oil-producing countries as well. Is it possible to limit the imputation process only for oil-producing countries? I have a similar problem with the data for the incomes for other resources (e.g. gas and coal). (3) If I would leave only oil-producing countries in my dataset before imputation, I suppose it might cause another problem. There are also other quantities of interest, both for oil- and non-oil-producing countries, for which I want to make imputations. Would it make any sense to make imputation with different subsets of my original dataset and merge them afterwards? Thank you very much in advance for your help. Best regards, Nurjamal Omurkanova -- Nurjamal Omurkanova M.A. Department of Politics and Management University of Konstanz Room D 229 P.O. Box 86 D-78457 Konstanz Germany Phone: +49-7531-88-2311 Fax: +49-7531-882774 nurjamal.omurkanova(a)uni-konstanz.de http://www.polver.uni-konstanz.de/en/gschneider/members-of-staff/nurjamal-o…

11 years, 11 months

Missing Data Course Using Amelia II

by Levente Littvay (CEU)

Dear All I hope nobody will mind this post (and apologies for possible cross-posting). I would like to call your attention to the 7th ECPR Summer School in Methods and Techniques week long course on Missing Data. The summer school is held in Ljubljana, Slovenia from Aug 6-10. The course will cover Amelia among other material. You can find information about the summer school here: http://new.ecprnet.eu/MethodSchools/SummerSchools.aspx And specifically about the course here: http://new.ecprnet.eu/MethodSchools/2012_Ljubljana/CourseOutlines/D2.pdf Please also note my other course on good social scientific practices titles: "Data Problems and Solutions. Social Science Statistics in Practice" is offered in the first week of the summer school (July 30-Aug 3). Info can be found here: http://new.ecprnet.eu/MethodSchools/2012_Ljubljana/CourseOutlines/C5.pdf Please let people know who might be interested in attending either of these (or any of the Summer School's) courses. Thanks Levi -- Levente Littvay, Assistant Professor Department of Political Science / Center for Network Science Central European University, Budapest, Hungary

11 years, 11 months

moPrep

by J. Dieleman

Hello, I'm getting the following error when I try to use moPrep with a proxy: Error in `[.data.frame`(mf, , proxyname) : undefined columns selected I've never used moPrep successfully with a proxy, nor could I find any example code that uses a proxy, so there is a really good chance I'm just specifying something wrong. Here is an example using the africa data provided with the package. moPrep works well without a proxy, but with "civlib" specified as a proxy, specified as it seems most natural to me, the command fails. > data(africa) > m.out <- moPrep(africa, trade ~ trade, error.proportion = 0.1) > exists("m.out") [1] TRUE > m.out.with.proxy <- moPrep(africa, trade ~ trade | civlib, error.proportion = 0.1) Error in `[.data.frame`(mf, , proxyname) : undefined columns selected > exists("m.out.with.proxy") [1] FALSE I'm using Amelia 1.6.1 on R 2.15.0, platform: x86_64-pc-mingw32/x64 (64-bit). Any help or pointers is appreciated. Thanks so much, Joe Dieleman

11 years, 11 months

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Amelia May 2012