In the second edition, we have added chapters on Bayesian inference in linear models (Chapter 11) and linear mixed models (Chapter 17), and have upgraded the material in all other …

Linear models can be used to explain or model the relationship between a response, or dependent, variable and one or more explanatory variables, or covariates or predictors. For …

1 Examples of the General Linear Model Complementary reading from Monahan: Chapter 1. at general form of a linear model is given by X = Y + ;

What if X and Y have a relationship, but it’s not linear? ---Note that the linear model is actually super flexible and can allow for all kinds of nonlinear relationships.

In addition to the specific distribution, need to specify a link function that describes how the mean of the response is related to a linear combination of predictors

The alternative model representations for these ANOVA and AN-COVA models make it clear that these are linear models. Let’s continue with matrix representation of these models.

Example 1.1 (Linear model for GDP). We consider the problem of building a linear model to pre-dict the gross domestic product (GDP) of a state in the US from its population and …