Introduction These are (incomplete) course notes about generalised linear mixed models (GLMM). Special emphasis is placed on understanding the underlying structure of a GLMM in order to show that slight modifications of this structure can produce a wide range of models. These include familiar models like regression and ANOVA, but also models with intimidating names: animal models, threshold mod...

Soil seed banks of alien plant species are sources propagules that play a crucial role in population dynamics. Studies on woody for understanding mechanisms their encroachment natural habitats. This study aimed to compare vertical distribution, density and composition formed by native Cornus sanguinea subsp. C. alba, sericea australis the Southern Hemiboreal zone Europe. Five sites each four ta...

Linear mixed-effect models (LMMs) are being increasingly widely used in psychology to analyse multi-level research designs. This feature allows LMMs to address some of the problems identified by Speelman and McGann (2013) about the use of mean data, because they do not average across individual responses. However, recent guidelines for using LMM to analyse skewed reaction time (RT) data collect...

Diagnostic test accuracy studies typically report the number of true positives, false positives, true negatives and false negatives. There usually exists a negative association between the number of true positives and true negatives, because studies that adopt less stringent criterion for declaring a test positive invoke higher sensitivities and lower specificities. A generalized linear mixed m...

To look for evidence of intrafamilial infection, we isolated 107 Helicobacter pylori clones from biopsied specimens taken from both parents and four children. We compared the sequences of two housekeeping genes (hspA and glmM) from these clones with those of 131 unrelated strains from patients living in different geographic regions. Strain relationships within the family were determined by anal...

Introduction Over the last decade, the application of syndromic surveillance systems has expanded beyond early event detection to include longterm disease trend monitoring. However, statistical methods employed for analyzing syndromic data tend to focus on early event detection. Generalized linear mixed models (GLMMs) may be a useful statistical framework for examining long-term disease trends ...

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...