I’m trying to select only one dataframe, after performing an imputation with
aregImpute and impute.transcan. However, I cannot get back a variable that was
kept out of the imputation model. Can somebody tell me how to do it? If we
illustrate this problem using the following reproducible example, how could I
get the dataframe with all the variables that were not imputated, such as
Species and id variables?
Best !
Data
data("iris")
library(missForest)
library(tidyverse)
library(Hmisc)
# example
iris.missing <- iris %>%
group_by(Species) %>%
prodNA(noNA = 0.1) %>%
ungroup() %>%
mutate(id=row_number())
imputation_model <- aregImpute(~Sepal.Length+Sepal.Width+Petal.Width,
n.impute=3,
data=iris.missing,
pr=F,
type='pmm')
data_imp <- impute.transcan(imputation_model,
imputation=1,
data=iris.missing,
list.out=TRUE,
pr=FALSE,
check=FALSE)
datos_imp <- bind_rows(data_imp)
--
Este mensaje le ha llegado mediante el servicio de correo electronico que
ofrece Infomed para respaldar el cumplimiento de las misiones del Sistema
Nacional de Salud. La persona que envia este correo asume el compromiso de usar
el servicio a tales fines y cumplir con las regulaciones establecidas
Infomed: http://www.sld.cu/
______________________________________________
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.
