Thanks Joris and pardon me for over assuming. let me add more information. My data is very huge and it is nested with repeated measurements. This is a sample of the dataset. id sex lang sch age chapt item length Resp 1 1 0 8 27.02095 3 1 4 0 1 1 0 8 27.02095 3 2 10 0 1 1 0 8 27.02095 1 3 10 0 1 1 0 8 27.02095 2 4 68 0 1 1 0 8 27.02095 2 5 63 NA 2 1 1 4 21.04946 3 1 4 NA 2 1 1 4 21.04946 3 2 10 1 2 1 1 4 21.04946 1 3 10 0 2 1 1 4 21.04946 2 4 68 NA 2 1 1 4 21.04946 2 5 63 NA 3 1 0 1 29.69218 3 1 4 NA 3 1 0 1 29.69218 3 2 10 1 3 1 0 1 29.69218 1 3 10 1 3 1 0 1 29.69218 2 4 68 1 3 1 0 1 29.69218 2 5 63 1 4 1 0 3 26.95328 3 1 4 0 4 1 0 3 26.95328 3 2 10 NA 4 1 0 3 26.95328 1 3 10 1 4 1 0 3 26.95328 2 4 68 0 4 1 0 3 26.95328 2 5 63 NA he imputation model and the model I am fitting are is as follows: imp <- mi(mydata,n.iter=6,n.imp=3, rand.imp.method="bootstrap", preprocess=F, run.past.convergence=F, check.coef.convergence=T,add.noise=F, post.run=F)
model <- lmer.mi(Resp~1+ sex + lang + age + length + (1|id) + (1|item)+ (1|sch) + (1|chapt),imp, family=binomial(link="logit")) print(modelmi) display(modelmi) After fitting a model, I can use display(model) to visualize the pooled estimates as well as estimates of each imputed dataset. I can visualize these also by typing print(model). However I would like to know how I can extract estimates of single imputed datasets. I have tried several commands for the first imputed dataset like mi.pooled$coefficients[[1]] , summary(model$analyses[[1]], etc etc but each do not work and i keep getting an error "object of type 'closure' is not subsettable" Hope this makes my question clear. Thanks -- View this message in context: http://r.789695.n4.nabble.com/Extract-estimates-from-each-dataset-MI-package-tp2259864p2260019.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.