Thank you very much to all of you for the responses!

Phil, the following two examples worked well in re-categorizing.  Is there
any way I can retain my original data.frame format?  Once I re-categorize
the data, the format becomes numeric and the original column names are not
retained.  I probably should have mentioned this earlier - I plan on using
the re-categorized data for coxph using the surv() function.

Here's how I am applying the re-categorization to my data:

*****************************************************************************

library(survival)
library(car)

gg <- read.table("k.csv", header=TRUE, sep = ",")
col = dim(genot)[2]

for(i in 1:col) {
aa<- recode(gg[,i], "c(1,2)='1'")
}

for(i in 1:col) {
dd<-factor(gg[,i],levels=0:2,labels=c('0','1','1'))
}


Thanks,
CC



On Sat, Jul 17, 2010 at 2:15 PM, Phil Spector <spector@stat.berkeley.edu>wrote:

> Please look at Peter Dalgaard's response a little more
> carefully.  There's a big difference between the levels=
> argument (which must be unique) and the labels= argument (which need not
> be).  Here are two ways
> to do what you want:
>
>  d = 0:2
>> factor(d,levels=0:2,labels=c('0','1','1'))
>>
> [1] 0 1 1
>
>> library(car)
>> recode(d,"c(1,2)='1'")
>>
> [1] 0 1 1
>
>
>                                        - Phil Spector
>                                         Statistical Computing Facility
>                                         Department of Statistics
>                                         UC Berkeley
>                                         spector@stat.berkeley.edu
>
>
>
>
-- 
Thanks,
CC

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