A fragment constant model for prediction of KOC was developed and evaluated with a diverse database of 592 chemicals belonging to 17 classes. The range of experimental KOC covered 7.65 log-units. The 592 chemicals were randomly divided into a training set and a testing set for model development and validation. A general model was then established using the entire database having 74 fragment con...

The authors consider the empirical likelihood method for the regression model of mean qualityadjusted lifetime with right censoring. They show that an empirical log-likelihood ratio for the vector of the regression parameters is asymptotically a weighted sum of independent chi-square distributions. They obtain an adjusted empirical log-likelihood ratio which is asymptotically standard chi-squar...

Log-concavity is an important property in the context of optimization, Laplace approximation, and sampling; Bayesian methods based on Gaussian process priors have become quite popular recently for classification, regression, density estimation, and point process intensity estimation. Here we prove that the predictive densities corresponding to each of these applications are log-concave, given a...

BACKGROUND Cross-sectional studies with binary outcomes analyzed by logistic regression are frequent in the epidemiological literature. However, the odds ratio can importantly overestimate the prevalence ratio, the measure of choice in these studies. Also, controlling for confounding is not equivalent for the two measures. In this paper we explore alternatives for modeling data of such studies ...

BACKGROUND Recent communications have argued that often it may not be appropriate to analyse cross-sectional studies of prevalent outcomes with logistic regression models. The purpose of this communication is to compare three methods that have been proposed for application to cross sectional studies: (1) a multiplicative generalized linear model, which we will call the log-binomial model, (2) a...

The most used regression model with binary dependent variable is the logistic regression model. When the dependent variable represents a rare event, the logistic regression model shows relevant drawbacks. In order to overcome these drawbacks we propose the Generalized Extreme Value (GEV) regression model. In particular, in a Generalized Linear Model (GLM) with binary dependent variable we sugge...

The effects of moderate restriction of dietary sodium and potassium supplementation on plasma levels of renin, angiotensin II, aldosterone, and cortisol and on arterial pressure were studied in 12 patients with mild essential hypertension. To define hormone-blood pressure relationships, venous hormone levels were measured hourly and intra-arterial pressure continuously for 24 hours after 4 to 6...