The general linear model (glm) provides a general framework for a large set of models whose common goal is to explain or predict a quantitative dependent variable by a set of independent variables which can be categorical of quantitative. The glm encompasses techniques such as Student’s t test, simple and multiple linear regression, analysis of variance, and covariance analysis. The glm is adeq...

The GLM procedure has been the workhorse for mixed model applications in the SAS® System. Other procedures, including NESTED and VARCOMP, are used for specific applications. Since its introduction in 1976, GLM has been enhanced with several mixed model facilities such as the RANDOM and REPEATED statements. However, there are aspects of certain models that none of these facilities fully accommod...

For a general cross-over design, combined intra-inter unit reduced normal equations for estimating linear functions of direct and residual effects are obtained under a mixed effects, non-additive model. The unit effects are considered as random and the model allows for possible interactions among treatments applied at successive periods. Several existing families of designs which are optimal un...

Robust supplier selection problem, in a scenario-based approach has been proposed, when the demand and exchange rates are subject to uncertainties. First, a deterministic multi-objective mixed integer linear programming is developed; then, the robust counterpart of the proposed mixed integer linear programming is presented using the recent extension in robust optimization theory. We discuss dec...

The penalized quasi-likelihood (PQL) approach is the most common estimation procedure for the generalized linear mixed model (GLMM). However, it has been noticed that the PQL tends to underestimate variance components as well as regression coefficients in the previous literature. In this paper, we numerically show that the biases of the variance components are systematically related to the bias...

Abstract We consider situations where a model for an ordered categorical response variable is deemed necessary. Standard models may not be suited to perform this analysis, being that the marginal probability effects large extent are predetermined by rigid parametric structure. propose use rank likelihood approach in non Gaussian framework and show how additional flexibility can gained modeling ...

Electrical stimulation of the skin using a needle-electrode specifically activates nociceptive nerve fibres. The detection of such stimuli by subjects depends on the activation of subsequent nociceptive mechanisms. Activation of these mechanisms depends on the temporal stimulus properties, such as the pulse-width, number of pulses, and inter-pulse interval. This different activation of nocicept...

The generalized linear mixed models (GLMMs) for clustered data are studied when covariates aremeasured with error. Themost conventional measurement error models are based on either linear mixed models (LMMs) or GLMMs. Even without the measurement error, the frequentist analysis of LMM, and particularly of GLMM, is computationally difficult. On the other hand, Bayesian analysis of LMM and GLMM i...

A study is presented showing how three state-of-the-art algorithms from the Face Recognition Vendor Test 2006 (FRVT 2006) are effected by factors related to face images and people. The recognition scenario compares highly controlled images to images taken of people as they stand before a camera in settings such as hallways and outdoors in front of buildings. A Generalized Linear Mixed Model (GL...