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, ...

In generalized linear models, the response is assumed to possess a probability distribution of the exponential form. That is, the probability density of the response Y for continuous response ...

This is the GEE equivalent of the inverse of the Fisher information matrix that is often used in generalized linear models as an estimator of the covariance estimate of the maximum likelihood ...

Logistic regression is a particular case of a generalized linear model. Like linear regression, logistic regression is a widely used statistical tool and one of the foundational tools for your data ...

Turkish insurer Neova Sigorta, in collaboration with data and artificial intelligence (AI) company SAS and SAS Partner Sade ...

2nd edition. Chapman & Hall. McCullagh, P. & Nelder, J.A. (1989) Generalized Linear Models. 2nd edition. Chapman & Hall. Agresti, A. (2015) Foundations of Linear and Generalized Linear Models. Wiley ...