The mixed model is written as where everything is the same as in the general linear model except for the addition of the known design matrix, Z, and the vector of unknown random-effects parameters,.

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, ...

The model-based estimator of is given by where 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 ...

Statistical approaches to overdispersion, correlated errors, shrinkage estimation, and smoothing of regression relationships may be encompassed within the framework of the generalized linear mixed ...

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, ...

It is well known that the ordinary least squares estimator of Xβ in the general linear model Ey = Xβ, cov y = σ2V, can be the best linear unbiased estimator even if V is not a multiple of the identity ...

Explore the fundamentals of the Finite Element Method (FEM), one of the most powerful computational tools used in engineering analysis. This introductory video breaks down the core concepts behind FEM ...

Topics include: general theory of regression and generalised linear models, linear regression, logistic regression for binary data, models for ordered and unordered (nominal) responses, log-linear ...