Thanks -- that's very helpful! -Don On Wed, May 28, 2008 at 4:34 PM, John Fox <[EMAIL PROTECTED]> wrote: > Dear Donald, > > I can't guarantee that there aren't other problems, but your call to > update() is in error; you need > > allmis <- update(allmis, white = recode(RACE, '1=1; else=0; ')) > > not > > allmis <- update(allmis, white <- recode(RACE, '1=1; else=0; ')) > > [The last ; in the recode specification is unnecessary, but should do no > harm; as well, for a simple recode like this you might prefer ifelse() to > recode().] > > Here's an example: > > --------- snip --------- > >> library(mitools) >> library(car) >> data(smi) >> smi <- update(smi, sex=recode(sex, "0 = 'M'; 1 = 'F'")) >> with(smi, table(sex, drkfre)) > [[1]] > drkfre > sex Non drinker not in last wk <3 days last wk >=3 days last wk > F 207 194 134 35 > M 282 201 105 12 > > [[2]] > drkfre > sex Non drinker not in last wk <3 days last wk >=3 days last wk > F 200 200 132 38 > M 282 195 109 14 > > . . . > > attr(,"call") > with.imputationList(smi, table(sex, drkfre)) > > ----------- snip ----------- > > I hope this helps, > John > > ------------------------------ > John Fox, Professor > Department of Sociology > McMaster University > Hamilton, Ontario, Canada > web: socserv.mcmaster.ca/jfox > >> -----Original Message----- >> From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] > On >> Behalf Of Donald Braman >> Sent: May-28-08 2:21 PM >> To: r-help@r-project.org >> Subject: [R] manipulating multiply imputed data sets >> >> Hi folks, >> >> I have five imputed data sets and would like to apply the same >> recoding routines to each. I could do this sort of thing pretty >> easily in Stata using MIM, but I've decided to go cold turkey on other >> stats packages as a incentive for learning more about R. Most of the >> recoding is for nominal variables, like race, religion, urbanicity, >> and the like. So, for example, to recode race for my first dataset, >> inmi1, I would do the following: >> >> miset1$white <- recode(miset1$RACE, '1=1; else=0; ') >> miset1$black <- recode(miset1$RACE, '2=1; else=0; ') >> miset1$asian <- recode(miset1$RACE, '3=1; else=0; ') >> miset1$hispanic <- recode(miset1$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 R references the original object and when it creates a new >> one. I suppose I could do this in Python and the use PyR, but I'd >> really like to learn a bit more about how R syntax. >> >> Any help on this specific problem or general advice on manipulating >> data in multiply imputed datasets in R would be much appreciated. >> >> -- >> Donald Braman >> http://www.law.gwu.edu/Faculty/profile.aspx?id=10123 >> http://research.yale.edu/culturalcognition >> http://ssrn.com/author=286206 >> >> ______________________________________________ >> 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. > >
-- Donald Braman http://www.law.gwu.edu/Faculty/profile.aspx?id=10123 http://research.yale.edu/culturalcognition http://ssrn.com/author=286206 ______________________________________________ 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.
