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...

The ongoing Small Area Income and Poverty Estimates (SAIPE) project at the Census Bureau estimates numbers of poor school-age children by state, county, and ultimately school district, based upon Current Population Survey (CPS) and IRS data along with information from the latest decennial census. The current SAIPE county-level methodology relies on a Fay-Herriot (1979) model fitted to log-count...

This paper examined the robustness of generalized linear mixed model (GLMM). The GLMM estimates fixed and random effects, it is especially useful when dependent variable binary. It also involves repeated measures, since can correlation. present study used Monte Carlo simulation to analyze empirical Type I error rates GLMMs in split-plot designs. variables manipulated were sample size, group num...

We introduce a flexible marginal modelling approach for statistical inference for clustered/longitudinal data under minimal assumptions. This estimated estimating equations (EEE) approach is semiparametric and the proposed models are fitted by quasi-likelihood regression, where the unknown marginal means are a function of the fixed-effects linear predictor with unknown smooth link, and variance...

Phosphoglucosamine mutase (GlmM) catalyzes the formation of glucosamine-1-phosphate from glucosamine-6-phosphate, an essential step in the pathway for UDP-N-acetylglucosamine biosynthesis in bacteria. This enzyme must be phosphorylated to be active and acts according to a ping-pong mechanism involving glucosamine-1, 6-diphosphate as an intermediate (L. Jolly, P. Ferrari, D. Blanot, J. van Heije...

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...

Maximum likelihood estimation for Generalized Linear Mixed Models (GLMM), an important class of statistical models with substantial applications in epidemiology, medical statistics, and many other fields, poses significant computational difficulties. In this article, we use data cloning, a simple computational method that exploits advances in Bayesian computation, in particular the Markov Chain...

Abstract Background Phenylketonuria (PKU) is an autosomal recessive inherited disorder characterised by a deficiency in phenylalanine hydroxylase. Untreated, PKU associated with wide range of cognitive and psychiatric sequelae. Contemporary management guidelines recommend lifetime dietary control (Phe) levels, however many individuals who discontinue subsequently suffer symptoms anxiety, depres...