Logo Questions Linux Laravel Mysql Ubuntu Git Menu
 

Contrasts can be applied only to factor

Tags:

variables

r

I have a question about R.

I am using a test called levene.test to test a homogeneity of variance.

I know that you need a factor variable with at least two levels in order for this to work. And from what I see, I do have at least two levels for the factor variable that I am using. But somehow I keep getting the error of:

> nocorlevene <- levene.test(geno1rs11809462$SIF1, geno1rs11809462$k, correction.method = "correction.factor")

    Error in `contrasts<-`(`*tmp*`, value = contr.funs[1 + isOF[nn]]) : 
      contrasts can be applied only to factors with 2 or more levels

I even try generate a variable from a binomial distribution:

k<-rbinom(1304, 1, 0.5)

and then use that as a factor, but is still not working.

Lastly I create a variable with 3 levels:

k<-sample(c(1,0,2), 1304, replace=T)

but some how still not working and getting the same error of:

nocorlevene <- levene.test(geno1rs11809462$SIF1, geno1rs11809462$k, correction.method="zero.removal")

Error in `contrasts<-`(`*tmp*`, value = contr.funs[1 + isOF[nn]]) : 
  contrasts can be applied only to factors with 2 or more levels

This is the output of the type of the variable in the data:

> str(geno1rs11809462)
'data.frame':   1304 obs. of  16 variables:
 $ id           : chr  "WG0012669-DNA_A03_K05743" "WG0012669-DNA_A04_K05752" "WG0012669-DNA_A05_K05761" "WG0012669-DNA_A06_K05785" ...
 $ rs11809462   : Factor w/ 2 levels "2/1","2/2": 2 2 2 2 2 2 2 2 2 2 ...
  ..- attr(*, "names")= chr  "WG0012669-DNA_A03_K05743" "WG0012669-DNA_A04_K05752" "WG0012669-DNA_A05_K05761" "WG0012669-DNA_A06_K05785" ...
 $ FID          : chr  "9370" "9024" "14291" "4126" ...
 $ AGE_CALC     : num  61 47 NA 62.5 55.6 59.7 46.6 41.2 NA 46.6 ...
 $ MREFSUM      : num  185 325 NA 211 212 ...
 $ NORSOUTH     : Factor w/ 3 levels "0","1","NA": 1 1 3 1 1 1 1 1 3 1 ...
 $ smoke1       : Factor w/ 3 levels "0","1","NA": 2 2 3 1 1 1 2 1 3 1 ...
 $ smoke2       : Factor w/ 3 levels "0","1","NA": 1 1 3 2 2 2 1 2 3 2 ...
 $ ANYCG60      : num  0 0 NA 1 0 0 0 0 NA 1 ...
 $ DCCT_HBA_MEAN: num  7.39 6.93 NA 7.37 7.56 7.86 6.22 8.88 NA 8.94 ...
 $ EDIC_HBA     : num  7.17 7.63 NA 8.66 9.68 7.74 6.59 9.34 NA 7.86 ...
 $ HBAEL        : num  7.3 8.82 NA 9.1 9.3 ...
 $ ELDTED_HBA   : num  7.23 7.76 NA 8.36 9.21 7.92 6.64 9.64 NA 9.09 ...
 $ SIF1         : num  19.6 17 NA 23.8 24.1 ...
 $ sex          : Factor w/ 2 levels "0","1": 1 1 2 2 2 2 1 1 1 1 ...
 $ k            : Factor w/ 3 levels "0","1","2": 1 1 2 3 1 3 3 3 1 2 ...

As you can see the variable k, sex have 3 and 2 levels respectively but somehow I still get that error message.

> head(geno1rs11809462)
                        id rs11809462   FID AGE_CALC  MREFSUM NORSOUTH smoke1 smoke2 ANYCG60
1 WG0012669-DNA_A03_K05743        2/2  9370     61.0 184.5925        0      1      0       0
2 WG0012669-DNA_A04_K05752        2/2  9024     47.0 325.0047        0      1      0       0
3 WG0012669-DNA_A05_K05761        2/2 14291       NA       NA       NA     NA     NA      NA
4 WG0012669-DNA_A06_K05785        2/2  4126     62.5 211.2557        0      0      1       1
5 WG0012669-DNA_A08_K05802        2/2 11280     55.6 212.2922        0      0      1       0
6 WG0012669-DNA_A09_K05811        2/2 11009     59.7 261.0116        0      0      1       0
  DCCT_HBA_MEAN EDIC_HBA HBAEL ELDTED_HBA    SIF1 sex k
1          7.39     7.17  7.30       7.23 19.6136   0 0
2          6.93     7.63  8.82       7.76 17.0375   0 0
3            NA       NA    NA         NA      NA   1 1
4          7.37     8.66  9.10       8.36 23.8333   1 2
5          7.56     9.68  9.30       9.21 24.1338   1 0
6          7.86     7.74  8.53       7.92 25.7272   1 2

If anyone can give me some hints as to why this is happening, it would be great. I just don't know why the variable k or sex or having different levels are giving me error when I run the test.

thank you

like image 923
john_w Avatar asked Dec 17 '13 22:12

john_w


1 Answers

I think I may have solved the problem. I believe it is due to NA value in the data. Because after I removed the na using say

x<-na.omit(original_data)

then apply the levene test on x, the warning message disappears.

Hopefully this is the cause of the problem.

like image 167
john_w Avatar answered Oct 19 '22 17:10

john_w