Hi All, I have a purely theoretical question on how to speciy (correctly, if possible) the error terms to use in a linear model with mixed effects. I have an experiment where I grow flies from 4 selection regimes at 2 temeratures. Each selection regime has 3 independent replicates. I summary: 2 temperatures 4 selection regimes 3 independent replicates per selection regime, for a grand total of 12. The replicates are coded 1:12 as a factor If I write dow the anova table, I have the following effects: d.f. temp 1 sel 3 sel/rep 8 temp*sel 3 temp*sel/rep 8 residuals If I am correct, the error terms are: temp over temp*sel/rep (the df are 1/8) sel over sel/rep (the df are 3/8) sel/rep over the residuals (the df are 8/residuals) temp*sel over temp*sel/rep (the df are 3/8) temp*sel/rep over the residuals (the df are 8/residuals) Using lme the model: anova(lme( measurement.taken ~ temp*sel, random = ~ 1|rep/temp, mydata)) gives an estimate with the right degrees of freedom for num and dem. But WHY do I have to nest tem inside rep? cannot figure it out for the life of me. If I want to use aov: anova(aov( measurement.taken ~ temp*sel + temp*sel/rep + sel/rep + Error ???, mydata)) How do I specify the correct error terms? ======================== Federico C.F. Calboli Department of Biology University College London Room 327 Darwin Building Gower Street London WClE 6BT Tel: (+44) 020 7679 4395 Fax (+44) 020 7679 7096 f.calboli at ucl.ac.uk