On Jan 27, 2012; 6:29pm Ben Bolker wrote: > My best (not very well-informed) guess is that there is something going > on with automatic dropping of terms > that appear to be aliased?? and that this test is (perhaps > unintentionally) order-dependent.
Looks to me like Ben is close to the mark here. From ?alias: "Complete aliasing refers to effects in linear models that cannot be estimated independently of the terms which occur earlier in the model and so have their coefficients omitted from the fit." > alias(m0, complete=T) Model : Y ~ A:B + x:A Complete : (Intercept) Aa1:Bb1 Aa2:Bb1 Aa1:Bb2 Aa2:Bb2 Aa1:Bb3 Aa2:Bb3 Aa1:Bb4 Aa1:x Aa2:x Aa2:Bb4 1 -1 -1 -1 -1 -1 -1 -1 0 0 > alias(m1, complete=T) Model : Y ~ x:A + A:B However, if you fit "proper" (or statistically sensible models), then there is no problem reversing terms: > logLik(m2 <- lm(Y ~ A*B + x*A, dat)) 'log Lik.' -13.22186 (df=11) > logLik(m3 <- lm(Y ~ x*A + A*B, dat)) 'log Lik.' -13.22186 (df=11) Regards, Mark Difford ----- Mark Difford (Ph.D.) Research Associate Botany Department Nelson Mandela Metropolitan University Port Elizabeth, South Africa -- View this message in context: http://r.789695.n4.nabble.com/Why-does-the-order-of-terms-in-a-formula-translate-into-different-models-model-matrices-tp4333408p4334385.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.