Multivariate models with random predictors are often considered in public health. Prospective power analysis for such models must take into account all possible stochastic realizations of the predictors. An extended definition is given for General Linear Multivariate Models with both random and fixed predictors. A classification scheme for hypotheses is introduced. Those that concern both fixed...

The objective of this study was to evaluate if a multi-sensor system (milk, activity, body posture) was a better classifier for lameness than the single-sensor-based detection models. Between September 2013 and August 2014, 3629 cow observations were collected on a commercial dairy farm in Belgium. Human locomotion scoring was used as reference for the model development and evaluation. Cow beha...

This study aims to compare the performance of data modeling with Poisson regression Generalized Linear Model (GLM), Mixed (GLMM), and Estimating Equation (GEE) modeling. The case used is a factor that affects number Pulmonary Tuberculosis cases in Indonesia panel data. Based on AIC criteria, smallest BIC RMSE GLMM models perform better than GLM GEE. In addition, also has coefficient determinati...

Five different PCR methods for the detection of Helicobacter pylori were evaluated. The results of this study indicate that of the five PCR methods examined, the ureC (glmM) gene PCR is the most sensitive and specific for the detection of H. pylori in gastric biopsy specimens.

We devise a classification algorithm based on generalised linear mixed model (GLMM) technology. The algorithm incorporates spline smoothing, additive model-type structures and model selection. For reasons of speed we employ the Laplace approximation, rather than Monte Carlo methods. Tests on real and simulated data show the algorithm to have good classification performance. Moreover, the result...

Abstract Spatio‐temporal maps of organismal density or relative abundance are fundamental to many applications in conservation and ecology. There often a number data sources inform species maps, including citizen science monitoring programs, remote sensing, geolocation from satellite‐tagged animals formal scientific surveys. In these cases, it may be desirable come up with single map integratin...

Today, generalized linear mixed models (GLMM) are broadly used in many fields. However, the development of tools for performing simultaneous inference has been largely neglected this domain. A framework joint is indispensable to carry out statistically valid multiple comparisons parameters interest between all or several clusters. We therefore develop confidence intervals and testing procedures...