statisticalrethinkin..

164 5. MULTIVARIATE LINEAR MODELSe model we aim to fit to the data is kcal.per.g regressed on the dummy variablesfor clade:k i ∼ Normal(µ i , σ)µ i = α + β NWM NWM i + β OWM OWM i + β S S iα ∼ Normal(0.6, 10)β NWM ∼ Normal(0, 1)β OWM ∼ Normal(0, 1)β S ∼ Normal(0, 1)σ ∼ Uniform(0, 10)A linear model like this really defines 4 different linear models, each corresponding to a differentcategory. A table might help you to understand how dummy variables make individualparameters contingent on category:Category NWM i OWM i S i µ iApe 0 0 0 µ i = αNew World monkey 1 0 0 µ i = α + β NWMOld World monkey 0 1 0 µ i = α + β OWMStrepsirrhine 0 0 1 µ i = α + β SEach category implies a different set of 1s and 0s in the dummy variables, which in turn implya different equation for µ i , once simplified.Fitting the model is straightforward:R code5.47m5.14