RE: Covariate models of genetic polymorphisms

From: "Bill Bachman" bachmanw@comcast.net Subject: RE: [NMusers] Covariate models of genetic polymorphisms Date: Thu, July 06, 2006 8:28 am The following comments apply to any covariates (as I have no experience with genetic markers as covariates): An argument can be made that multiplicative parameterizations are sometimes found to be easier to get to converge than the linear counterpart (possibly they are more descriptive of the mathematical relationships found in nature or that they code for a fractional change in the parameter rather than a strictly additive component to the parameter). Many go one step further and use multiplicative exponential parameterization that better codes for nonlinear relationships. If you use the linear parameterization and want to test for interaction, add another term: something like this GRPCL=POP_CL*SizeDescriptor+FGene1+FGene2+FGene1*FGene2 Possibly the best advice I could give is: try the variations yourself. Others experience is nice to know, but nothing beats testing your hypotheses yourself.