[R] Discriminant Function Analysis

[Uwe Ligges]

michael watson (IAH-C) wrote:

> Thanks for the answers Uwe!
> 
> So this is a common problem in biology - few number of cases and many,
> many variables (genes, proteins, metabolites, etc etc)! 
> 
> Under these conditions, is discriminant function analysis not an ideal
> method to use then?  Are there alternatives?

No, obviously not "an ideal method", if used as is on the whole data.

Alternatives are certainly described in the literature - I am not 
specialised in this field (I mean, this gene stuff), hence do not want 
to specify misleading references here.

Uwe Ligges


> 
>>1) First problem, I got this error message:
>>
>>
>>>z <- lda(C0GRP_NA ~ ., dpi30)
>>
>>Warning message:
>>variables are collinear in: lda.default(x, grouping, ...) 
>>
>>I guess this is not a good thing, however, I *did* get a result and it
> 
> 
>>discriminated perfectly between my groups.  Can anyone explain what 
>>this means?  Does it invalidate my results?
> 
> 
> Well, 14 cases and 37 variables mean that not that many degrees of 
> freedom are left.... ;-)
> Of course, you get a perfect fit - with arbitrary data.