Displaying 2 results from an estimated 2 matches for "allmis".
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allis
2008 May 28
1
manipulating multiply imputed data sets
...ic <- recode(miset1$RACE, '4=1; else=0; ')
miset1$raceother <- recode(miset1$RACE, '5=1; else=0; ')
I've tried a number of variations, e.g., on the following using recode
(from the car package) with imputationList (from the mitools package),
though without success:
files.allmisets <- list.files(getwd(),pattern="miset*.csv$",full=TRUE)
allmis <- imputationList(lapply(files.allmisets, read.csv))
allmis <- update(allmis, white <- recode(RACE, '1=1; else=0; '))
I've also tried some basic loops. I guess I'm also a bit confused as
to when...
2008 May 30
0
imputationlist, update, and recode
...un into trouble,
though, when I try to construct a scale across all the data sets. Is there
a simple way to do this?
(here's what I've been trying)
vars_to_impute = c("var1", ... "var50")
imputed <- amelia(data=vars_to_impute, m=5, outname="miset")
files.allmisets <- list.files(getwd(),pattern="miset*",full=TRUE)
allmis <- imputationList(lapply(files.allmisets, read.csv))
scale1_vars <- c("var1", "var2", "var3", ... "var20")
scale2_vars <- c("var21", "var22", "var23&qu...