Re: [amelia] Amelia Error Code 32

Dear Matt, I greatly appreciate you response. Below is (essentially) the code I am running (I have a function "mk_imp_df" that subsets the original data frame into a smaller one for the imputations). When I say "essentially" the code I am using, I mean I am omitting a much longer list of variables (~25 variables). The 'offending' variables are simple continuous variables (floats on the scale from 0->1) and I think they are properly recognized/classified by R... Please let me know if I can offer any further information! Thank you again for your time and help! All the best, Ryan nImp=10 ivars <- c('idc', 'iq_5', 'age_yrs', 'sex_int', 'sum_ext_5', 'sum_int_5', 'cbcl_sum_5') exclude_ivars <- c('idc', 'iq_5') imp_df <- mk_imp_df(ivars, orig_dataFrame) #does not work...gives the error code 32 amelia_imp <- amelia(imp_df, m=nImp, idvars=exclude_ivars) #Works amelia_imp <- amelia(imp_df, m=nImp, idvars=exclude_ivars, incheck=FALSE) On Apr 5, 2015, at 4:05 PM, Matt Blackwell &lt;mblackwell(a)gov.harvard.edu&gt; wrote: for example, both "idvars" and "logs" in the same call to amelia. Can you send the code you are using to call amelia? It might help us diagnose the problem. options for working around it. combinations of each other. Thus, they all cannot be in the imputation model. I am using the "idvars" argument to hold one of these variables out of the imputation process to avoid the "error: inv_sympd(): matrix appears to be singular" message, which I think is related to the fact that these variables are related. imputations using the "idvars" argument, I get the message below: imputation, but one left out using "idvars", and specifying incheck=FALSE variables from the imputation...so it is only failing when I also add one of these 4 correlated variables. imputation process, but are important for the stats I would like to run down the road on the imputed data (thus I need them in the final imputed data set). When I put all 4 of the variables into the "idvars" argument, I get the error related to the number of excluded variables >> number of variables used for imputation. you!