In mice package for extract complete dataset you can use complete() command as follow :
install.packages("mice")
library ("mice")
imp1=mice(nhanes,10)
fill1=complete(imp,1)
fill2=complete(imp,2)
fillall=complete(imp,"long")
But can some one tell me how to extract complete dataset in Amelia package??
install.packages("Amelia")
library ("Amelia")
imp2= amelia(freetrade, m = 5, ts = "year", cs = "country")
The str() function is always helpful here. You'll see that the complete datasets are stored in the imputations element of the object returned by amelia():
> str(imp2, 1)
List of 12
$ imputations:List of 5
..- attr(*, "class")= chr [1:2] "mi" "list"
$ m : num 5
$ missMatrix : logi [1:171, 1:10] FALSE FALSE FALSE FALSE FALSE FALSE ...
..- attr(*, "dimnames")=List of 2
$ overvalues : NULL
$ theta : num [1:9, 1:9, 1:5] -1 -0.0161 0.199 -0.0368 -0.0868 ...
$ mu : num [1:8, 1:5] -0.0161 0.199 -0.0368 -0.0868 -0.0658 ...
$ covMatrices: num [1:8, 1:8, 1:5] 0.8997 -0.3077 0.0926 0.2206 -0.1115 ...
$ code : num 1
$ message : chr "Normal EM convergence."
$ iterHist :List of 5
$ arguments :List of 23
..- attr(*, "class")= chr [1:2] "ameliaArgs" "list"
$ orig.vars : chr [1:10] "year" "country" "tariff" "polity" ...
- attr(*, "class")= chr "amelia"
To get each imputation alone, just do imp2$imputations[[1]], etc. up through all imputations that you requested. In your example, there are five:
> str(imp2$imputations, 1)
List of 5
$ imp1:'data.frame': 171 obs. of 10 variables:
$ imp2:'data.frame': 171 obs. of 10 variables:
$ imp3:'data.frame': 171 obs. of 10 variables:
$ imp4:'data.frame': 171 obs. of 10 variables:
$ imp5:'data.frame': 171 obs. of 10 variables:
- attr(*, "class")= chr [1:2] "mi" "list"