[R] How to Get Categorical Correlation Coefficient

[Kum-Hoe Hwang]

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
> 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
>
---------------------------------------------------------------------------------------
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