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 <[email protected]> [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 > [email protected] > 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. _______________________________________________ R-lang mailing list [email protected] http://pidgin.ucsd.edu/mailman/listinfo/r-lang
