Hi I am unable to impute using the MICE command in R when imputing a binary variable using linear discriminant analysis. To illustrate my problem I have created a dataset, which consists of 1 continuous and 1 binary variable. The continuous variable is complete and the binary variable is partially observed.
I am able to impute using the MICE command where the imputation methods is logistic regression (option logreg). However I have been unsuccessful when I've tried to impute the binary variable using linear discriminant analysis (option lda) Instead I get the following error message "Error in colMeans(as.matrix(imp[[visitSequence[j]]])) : 'x' must be numeric" I can however impute using the elementary imputation method "impute.lda". Please upload the example dataset "mice_univariate.txt" from: https://www.bris.ac.uk/fluff/u/epzrah/wO7LD4sIw1qqwPO_kTakLAsW/ Please upload the R code "multiple_imputation_univariate.R" from: https://www.bris.ac.uk/fluff/u/epzrah/KyjUMRptLAI_fShpzGHDsQsW/ The dataset I would like to apply the command to has missingness on more than one variable. Therefore I need to use the MICE command. Your help would be much appreciated Kind Regards Rachael Hughes ---------------------- RA Hughes [EMAIL PROTECTED] ______________________________________________ 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.
