mice: selecting small subset of variables to impute from dataset with many variables (> 2500)

Maybe this is too simple but could you use the select() function from dplyr?
Tim

-----Original Message-----
From: R-help <r-help-bounces at r-project.org> On Behalf Of Bert Gunter
Sent: Thursday, July 14, 2022 2:10 PM
To: Ian McPhail <ivmcphail at gmail.com>
Cc: R-help <r-help at r-project.org>
Subject: Re: [R] mice: selecting small subset of variables to impute from dataset with many variables (> 2500)

[External Email]

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

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 at r-project.org mailing list -- To UNSUBSCRIBE and more, see 
https://urldefense.proofpoint.com/v2/url?u=https-3A__stat.ethz.ch_mail
man_listinfo_r-2Dhelp&d=DwICAg&c=sJ6xIWYx-zLMB3EPkvcnVg&r=9PEhQh2kVeAs
Rzsn7AkP-g&m=UxEz20f8LSF-iyVuq17UnoNVkEe6HoC3E6vHWssLjSBKtqLSrm7qs8v2e
wcXchwc&s=ABj_L_b515lhH7RIgTmmjylyWxJCbRWvzZDkxUkGw90&e=
PLEASE do read the posting guide 
https://urldefense.proofpoint.com/v2/url?u=http-3A__www.R-2Dproject.or
g_posting-2Dguide.html&d=DwICAg&c=sJ6xIWYx-zLMB3EPkvcnVg&r=9PEhQh2kVeA
sRzsn7AkP-g&m=UxEz20f8LSF-iyVuq17UnoNVkEe6HoC3E6vHWssLjSBKtqLSrm7qs8v2
ewcXchwc&s=LiocKPLYgq5olAT6tqGjr2xOLwDWw55DRzhuq7gcF5A&e=
and provide commented, minimal, self-contained, reproducible code.

______________________________________________
R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://urldefense.proofpoint.com/v2/url?u=https-3A__stat.ethz.ch_mailman_listinfo_r-2Dhelp&d=DwICAg&c=sJ6xIWYx-zLMB3EPkvcnVg&r=9PEhQh2kVeAsRzsn7AkP-g&m=UxEz20f8LSF-iyVuq17UnoNVkEe6HoC3E6vHWssLjSBKtqLSrm7qs8v2ewcXchwc&s=ABj_L_b515lhH7RIgTmmjylyWxJCbRWvzZDkxUkGw90&e=
PLEASE do read the posting guide https://urldefense.proofpoint.com/v2/url?u=http-3A__www.R-2Dproject.org_posting-2Dguide.html&d=DwICAg&c=sJ6xIWYx-zLMB3EPkvcnVg&r=9PEhQh2kVeAsRzsn7AkP-g&m=UxEz20f8LSF-iyVuq17UnoNVkEe6HoC3E6vHWssLjSBKtqLSrm7qs8v2ewcXchwc&s=LiocKPLYgq5olAT6tqGjr2xOLwDWw55DRzhuq7gcF5A&e=
and provide commented, minimal, self-contained, reproducible code.