Now that you've got a good sense of how to 'speak' R, let's use it with linear regression to make distinctive predictions.

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Generalized Linear Models Generalized Linear Models Course Topics Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, ...

The sums of squares are described using the R () notation as applied to the over-parameterized linear model, but the hypotheses are stated in terms of the full-rank cell means model. The zero-cell ...

Generalised linear models; the exponential family, the linear predictor, link functions, analysis of deviance, parameter estimation, deviance residuals. Model choice, fitting and validation.

Dalei Yu, Xinyu Zhang, Kelvin K.W. Yau, Asymptotic properties and information criteria for misspecified generalized linear mixed models, Journal of the Royal Statistical Society.