Suppose I have a mixed-effects model where yij is the jth sample for the ith subject: yij= beta0 + beta1(age) + beta2(age^2) + beta3(age^3) + beta4(IQ) + beta5(IQ^2) + beta6(age*IQ) + beta7(age^2*IQ) + beta8(age^3 *IQ) +random intercepti + eij In R how can I get an F test against the null hypothesis of beta6=beta7=beta8=0? In SAS I can run something like contrast age*IQ 1, age^2*IQ 1, age^3 *IQ 1, but is there anything similar in R? Thanks in advance, Gang [[alternative HTML version deleted]]
Gang Chen <gangchen <at> mail.nih.gov> writes:> > Suppose I have a mixed-effects model where yij is the jth sample for > the ith subject: > > yij= beta0 + beta1(age) + beta2(age^2) + beta3(age^3) + beta4(IQ) + > beta5(IQ^2) + beta6(age*IQ) + beta7(age^2*IQ) + beta8(age^3 *IQ) > +random intercepti + eij > > In R how can I get an F test against the null hypothesis of > beta6=beta7=beta8=0? In SAS I can run something like contrast age*IQ > 1, age^2*IQ 1, age^3 *IQ 1, but is there anything similar in R?Check packages multcomp and gmodels for contrast tests that work with lme. Dieter