statisticalrethinkin..

4.4. ADDING A PREDICTOR 111precis( m4.3 , corr=TRUE )R code4.38Mean StdDev 2.5% 97.5% a sigma ba 113.89 1.91 110.16 117.63 1.00 0 -0.99sigma 5.07 0.19 4.70 5.45 0.00 1 0.00b 0.90 0.04 0.82 0.99 -0.99 0 1.00e new columns on the far right show the correlations among the parameters. is is thesame information you’d get by using cov2cor(vcov(m4.3)). Notice that α and β are almostperfectly negatively correlated. Right now, this is harmless. It just means that thesetwo parameters carry the same information—as you change the slope of the line, the bestintercept changes to match it. But in more complex models, strong correlations like this canmake it difficult to fit the model to the data. So we’ll want to use some golem engineeringtricks to avoid it, when possible.e first trick is CENTERING. Centering is the procedure of subtracting the mean of avariable from each value. To create a centered version of the weight variable:d2$weight.c