Many 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 treated with ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with two-way interactions between ...

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 66, No. 4 (2004), pp. 893-908 (16 pages) Generalized linear latent variable models (GLLVMs), as defined by ...

Mixed linear models are used to analyze data in many settings. These models have a multivariate normal formulation in most cases. The maximum likelihood estimator (MLE) or the residual MLE (REML) is ...

Diet models based on goal programming (GP) are valuable tools in designing diets that comply with nutritional, palatability and cost constraints. Results derived from GP models are usually very ...