[R] How to Get Categorical Correlation Coefficient

[Peter Dalgaard]

"Kum-Hoe Hwang" <phdhwang at gmail.com> writes:

> There was my mistake in the earlier email.
> I have corrected the error by dropping "ns.omit" from data.frame().
> 
> I added a new corrected correlation and output followings:
> 
> ------------------------------------------------------------------------------
> #
> > nrow(sdi)
> [1] 65613
> 
> > print(corridor1[65600:65613])
>  [1] C  C  C  C  F
>  [6] F  F  F  B  B
> [11] F F B  B
> Levels: B C D E A F
> 
> > print(corridor2[65600:65613])
>  [1] 4 4 4 4 2 2 2 2 1 1 2 2 1 1
> 
> > summary(corridor1)
>           B              C                D             E
>  A             F
>        15092        13456         6652         1611         1796        27006
> > summary(corridor2)
>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
>     0.0     1.0     2.0     2.3     3.0     5.0
> 
> > summary(as.numeric(as.factor(corridor1))-as.numeric(as.factor(corridor1)))
>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
>       0       0       0       0       0       0

One term of course needs to have corridor2. (That's my typo, but...) 



> > table(corridor1,corridor2)
>               corridor2
> corridor1          0     1     2     3     4     5
>   B       0 15092     0     0     0     0
>   C       0     0     0     0 13456     0
>   D       0     0     0  6652     0     0
>   E       0     0     0     0     0  1611
>   A      1796     0     0     0     0     0
>   F     0     0 27006     0     0     0


Notice that they are not in the same order! as.numeric(corridor1) will
have 1 for B, ..., 5 for A, 6 for F



> ---------------------------------------------------------------------------------------
> There are different correlation coefficients from the following results:
> Are there any functions or packages for a categorical correlation?
> 
> > cor(jh1_1, corridor1)
> [1] 0.02753303
> > cor(jh1_1, as.factor(corridor2))
> [1] -0.3682788
> 
> 
> Thanks for your kindness,
> 
> Kum
> 
> 
> On 12 Oct 2006 10:25:33 +0200, Peter Dalgaard <p.dalgaard at biostat.ku.dk> wrote:
> > "Kum-Hoe Hwang" <phdhwang at gmail.com> writes:
> >
> > > Howdy Gurus !
> > >
> > > I have a different correlation result from the same data. The
> > > "corridor1" string variable is expressed
> > > as a number like the "corridor2" number variable.
> > > --------------------------------------------------------------------------
> > > > levels(corridor1)
> > > [1] "A"   "B"   "C"   "D"     "E"   "F"
> > > > levels(as.factor(corridor2))
> > > [1] "0" "1" "2" "3" "4"
> > > >
> > > ------------------------------------------------------------------------------------------
> > > I have the correlation results followings using cor() function.
> > > ------------------------------------------------------------------------------------------
> > > > cor(jh1_1, as.factor(corridor1))
> > > [1] 0.01528538
> > > > cor(jh1_1, as.factor(corridor2))
> > > [1] -0.4972571
> > > ------------------------------------------------------------------------------------------
> > > I donot know why the above correlation coefficients used the same data
> > > are different.
> > > They are 0.015 from as.factor(corridor1), -0.497 from as,factor(corridor2).
> > > The string variable "corridor1" is the same catergory data with the
> > > variable corridor2.
> > > The difference is that "A" is replaced with "0", "B" with "1", "C"
> > > with "2", .....
> > >
> > > Could you tell me why they are different, and which correlation
> > > coefficient is correct?
> >
> > One thing that strikes me is that corridor1 has 6 levels and corridor2
> > has 5...
> >
> > In general correlations are not expected to work on factors so I'd be
> > explicit about taking as.numeric(). A glance at
> > table(corridor1,corridor2) should be informative too, as would a
> > summary(as.numeric(as.factor(corridor1))-as.numeric(as.factor(corridor1)))
> >
> > --
> >   O__  ---- Peter Dalgaard             Øster Farimagsgade 5, Entr.B
> >  c/ /'_ --- Dept. of Biostatistics     PO Box 2099, 1014 Cph. K
> >  (*) \(*) -- University of Copenhagen   Denmark          Ph:  (+45) 35327918
> > ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)                  FAX: (+45) 35327907
> >
> 
> 
> -- 
> Kum-Hoe Hwang, Ph.D.Phone : 82-31-250-3516Email : phdhwang at gmail.com
> 

-- 
   O__  ---- Peter Dalgaard             Øster Farimagsgade 5, Entr.B
  c/ /'_ --- Dept. of Biostatistics     PO Box 2099, 1014 Cph. K
 (*) \(*) -- University of Copenhagen   Denmark          Ph:  (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)                  FAX: (+45) 35327907