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Possible Duplicate:
dropping factor levels in a subsetted data frame in R

I have a data frame with several variables that I'm running a mixed model on using lme(). One of the variables, ForAgeCat, has five factor levels: 1,2,3,4,5. 

str(mvthab.3hr.fc$ForAgeCat)
 >Factor w/ 5 levels "1","2","3","4",..: 5 5 5 5 5 5 5 5 5 5 ...

The problem is that factor level 3 actually doesn't exist, that is, in this dataset (which is a subset of a larger dataset) there are no observations from factor level 3, which I think is messing with my modeling in lme(). Can someone help me to remove/eliminate factor level 3 from the list of factor levels?

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Luke
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1 Answers1

5

use the function droplevels, like so:

> DF$factor_var = droplevels(DF$factor_var)

More detail:

> # create a sample dataframe:
> col1 = runif(10)
> col1
    [1] 0.6971600 0.1649196 0.5451907 0.9660817 0.8207766 0.9527764 
        0.9643410 0.2179709 0.9302741 0.4195046
> col2 = gl(n=2, k=5, labels=c("M", "F"))
> col2
    [1] M M M M M F F F F F
    Levels: M F
> DF = data.frame(Col1=col1, Col2=col2)
> DF
     Col1 Col2
 1  0.697    M
 2  0.165    M
 3  0.545    M
 4  0.966    M
 5  0.821    M
 6  0.953    F
 7  0.964    F
 8  0.218    F
 9  0.930    F
 10 0.420    F

> # now filter DF so that only *one* factor value remains
> DF1 = DF[DF$Col2=="M",]
> DF1
   Col1 Col2
1 0.697    M
2 0.165    M
3 0.545    M
4 0.966    M
5 0.821    M

> str(DF1)
    'data.frame':   5 obs. of  2 variables:
   $ Col1: num  0.697 0.165 0.545 0.966 0.821
   $ Col2: Factor w/ 2 levels "M","F": 1 1 1 1 1

> # but still 2 factor *levels*, even though only one value

> DF1$Col2 = droplevels(DF1$Col2)
> # now Col2 has only a single level:
> str(DF1)
   'data.frame':    5 obs. of  2 variables:
  $ Col1: num  0.697 0.165 0.545 0.966 0.821
  $ Col2: Factor w/ 1 level "M": 1 1 1 1 1
doug
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