statisticalrethinkin..

232 7. INTERACTIONSe main effect likelihood is (we’ll add priors later):And the full interaction likelihood is:B i ∼ Normal(µ i , σ)µ i = α + β w w i + β s s iB i ∼ Normal(µ i , σ)µ i = α + β w w i + β s s i + β ws w i s iwhere B i is the value of bloom on row i, w i is the value of water, and s i is the value of shade.I’m leaving the categorical variable bed out of this analysis, but I actually think a sincereanalysis requires it, and in a later chapter, we’ll come back and add bed to the analysis. epoints I wish to make right now don’t depend upon it, however.Fitting the models with map is just as you might expect. I’ll use practically flat priorshere, so we get results nearly identical to typical maximum likelihood inference. is isn’t toimply that this is necessarily the best thing to do. Instead, it’s to present another example ofhow to do it.R code7.19m7.6