If I understand your query correctly, you can use negative indexing to omit variables. See ?'[' for details.
> dat <- data.frame (a = 1:3, b = letters[1:3], c = 4:6, d = letters[5:7]) > dat a b c d 1 1 a 4 e 2 2 b 5 f 3 3 c 6 g > dat[,-c(2,4)] a c 1 1 4 2 2 5 3 3 6 Of course you have to know the numerical index of the columns you wish to omit, but somethingh of the sort seems unavoidable in any case. Cheers, Bert On Thu, Jul 14, 2022 at 11:00 AM Ian McPhail <ivmcph...@gmail.com> wrote: > > Hello, > > I am looking for some advice on how to select subsets of variables for > imputing when using the mice package. > > From Van Buuren's original mice paper, I see that selecting variables to be > 'skipped' in an imputation can be written as: > > ini <- mice(nhanes2, maxit = 0, print = FALSE) > pred <- ini$pred > pred[, "bmi"] <- 0 > meth <- ini$meth > meth["bmi"] <- "" > > With the last two lines specifying the the "bmi" variable gets skipped over > and not imputed. > > And I have come across other examples, but all that I have seen lay out a > method of skipping variables where EVERY variable is named (as "bmi" is > named above). I am wondering if there is a reasonably easy way to select > out approximately 30 variables for imputation from a larger dataset with > around 2500 variables, without having to name all 2450+ other variables. > > Thank you, > > Ian > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
