Use of general linear mixed models (GLMMs) in genetic variance analysis can quantify the relative contribution of additive effects from genetic variation on a given trait. Here, Jonathan Mosley ...

The mixed effects model for binary responses due to Conaway (1990, A Random Effects Model for Binary Data) is extended to accommodate ordinal responses in general and discrete time survival data with ...

This paper presents mixed-signal block and IC-level verification methodologies using analog behavioral modeling and combined analog and digital solvers. It then describes analog real number modeling ...

This paper reports the results of an extensive Monte Carlo study of the distribution of the likelihood ratio test statistic using the value of the restricted likelihood for testing random components ...

Milliken and Johnson (1984) present an example of an unbalanced mixed model. Three machines, which are considered as a fixed effect, and six employees, which are considered a random effect, are ...

The focus of the standard linear model is to model the mean of y by using the fixed-effects parameters . The residual errors are assumed to be independent and identically distributed Gaussian random ...

Creating behavioral models is onlyone part of the process of using thosemodels in a mixed-signal verification flow.If the model and implementation do notmatch, the effort is worthless; worse, itcan ...