[R-lang] Collinearity and condition number

[Matthew Roberts]

Are you sure that the numeric values are the same in each case? When R
converts factor() to numeric(), it take the numerical factor id rather
than the name. To avoid this do:

numeric.condition.number <- as.numeric(as.character(factor.condition.number))

Hope this helps,

Matthew

* Claire Delle Luche <Claire.Delleluche at univ-lyon2.fr> [2009-04-20 10:41:58 +0200]:

> Dear R-users,
> 
> I am running a mixed effect model on a written corpus.
> When I check for collinearity, I get a value of 35 for condition number when my predictors are entered as names then transformed as numeric (the values are 1 and 2 for two level predictors after the transormation).
> However, when I enter the predictors as factors and assign levels of 0 and 1 instead of names (and convert them as numeric), I get a condition number of 12.
> 
> For the same data, depending on how I code the predictors, I either have moderate or important collinearity. What shall I do?
> Which coding is more acceptable?
> 
> Thanks very much in advance.
> 
> Yours,
> 
> Claire Delle Luche
> Laboratoire Dynamique du Langage
> 14, avenue Berthelot
> 69 007 Lyon
> France
> 
> _______________________________________________
> R-lang mailing list
> R-lang at ling.ucsd.edu
> http://pidgin.ucsd.edu/mailman/listinfo/r-lang
> 

-- 
Matthew A. J. Roberts
Department of Psychology,
University of Edinburgh,
7 George Square
EH8 9JZ
+44 (0)131 6511302
--

The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.