RE: [amelia] infinite or missing values in 'x'�

From: blackwel(a)fas.harvard.edu Date: Wed, 26 May 2010 14:44:03 -0400 Subject: Re: [amelia] infinite or missing values in 'x'ş To: wnuzzo(a)hotmail.com CC: amelia(a)lists.gking.harvard.edu Hi Wendy, Sorry for taking so long to get back to you. This feels like a numerical problem stemming from some variables being linear transformations of one another. You may want to track down the problematic variable by including variables one at a time (perhaps using a for loop). Another problem might be the number of parameters for the number of cases that you have. 69 variables implies roughly 2300 parameters and that is close to the number of observations you have. Cheers, matt. 2010/5/13 Wendy Nuzzo &lt;wnuzzo(a)hotmail.com&gt;om>: > Hello! > > I am having an issue running Amelia to impute missing dichotomous variables > (listed under "ords" below). My data set has n=2628 and 69 variables with > missing data. For about half of the variables, the missingness is less than > 20%. For the other half of the variables, the missingness is between 30% > and 40%. I have updated R & Amelia on my Mac: R 2.11.0 and Amelia 1.2-17. > > This is the code I'm running: > > az.out<-amelia(x=dat, m=5, > p2s=2,ords=c("recid","gender","bin_race","pf2_1","pf2_7","pf3_1","pf3_4","pf3_6","pf4_5","pf4_16","pf5_1","pf5_10","r2_2","r2_3","r2_4","r2_5","r2_8","r3_2","r3_3","r4_1","r4_3","r4_9","r4_10","r4_12","r4_14","r4_15","r5_2","r5_3","r5_4","r5_6","r5_7","r5_8","r6_1","r6_2","r6_3","r6_4","ipf2_1","ipf2_7","ipf3_1","ipf3_4","ipf3_6","ipf4_5","ipf4_16","ipf5_1","ipf5_10","ir2_2","ir2_3","ir2_4","ir2_5","ir2_8","ir3_2","ir3_3","ir4_1","ir4_3","ir4_9","ir4_10","ir4_12","ir4_14","ir4_15","ir5_2","ir5_3","ir5_4","ir5_6","ir5_7","ir5_8","ir6_1","ir6_2","ir6_3","ir6_4"), > idvars=c("recidcount")) > > And this is the error it results in: > > amelia starting > beginning prep functions > Variables used: recid age gender bin_race pf2_1 pf2_7 pf3_1 pf3_4 pf3_6 > pf4_5 pf4_16 pf5_1 pf5_10 r2_2 r2_3 r2_4 r2_5 r2_8 r3_2 r3_3 r4_1 r4_3 r4_9 > r4_10 r4_12 r4_14 r4_15 r5_2 r5_3 r5_4 r5_6 r5_7 r5_8 r6_1 r6_2 r6_3 r6_4 > ipf2_1 ipf2_7 ipf3_1 ipf3_4 ipf3_6 ipf4_5 ipf4_16 ipf5_1 ipf5_10 ir2_2 ir2_3 > ir2_4 ir2_5 ir2_8 ir3_2 ir3_3 ir4_1 ir4_3 ir4_9 ir4_10 ir4_12 ir4_14 ir4_15 > ir5_2 ir5_3 ir5_4 ir5_6 ir5_7 ir5_8 ir6_1 ir6_2 ir6_3 ir6_4 > running bootstrap > -- Imputation 1 -- > setting up EM chain indicies > > 1Error in eigen(thetanew[2:nrow(thetanew), 2:ncol(thetanew)], only.values = > TRUE, : > infinite or missing values in 'x' > > I was concerned about collinearity, so I calculated the VIFs and removed the > variables with high VIFs. Now all the variables have VIF < 10. I've also > tried a ridge prior of up to 300 to account for the high missingness rate. > I've looked in the listserv archives and of course "googled" my error as > well. > > Any guidance on what might be causing this error would be appreciated. > Thank you! > > Wendy Nuzzo > soon-to-be M.S. Stat > Portland State University > > ________________________________ > Hotmail has tools for the New Busy. Search, chat and e-mail from your inbox. > Learn more.