Duration: 12h. 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 ...

What is a Generalized Linear Model? A traditional linear model is of the form where y i is the response variable for the i th observation. The quantity x i is a column vector of covariates, or ...

Course TopicsMany response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after ...

The following is an algorithm for fitting the specified model using GEEs. Note that this is not in general a likelihood-based method of estimation, so that inferences based on likelihoods are not ...

What we expect to gain by applying a one-sided test instead of a two-sided test is an increase in the power of the test. We consider various tests of one-sided hypotheses in a class of models that ...

W. K. Li, Time Series Models Based on Generalized Linear Models: Some Further Results, Biometrics, Vol. 50, No. 2 (Jun., 1994), pp. 506-511 Free online reading for over 10 million articles Save and ...

The new approach recognizes the discrete nature of ignition counts by using generalized linear and generalized linear mixed models for the first time in this type of application. It includes careful ...