A bivariate regression model for matched paired survival data: local influence and residual analysis

The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.

Are biofuels a feasible option?

Recently a number of objections have been raised against the use of ethanol produced from agricultural products such as maize, sugarcane, wheat or sugar beets as a replacement for gasoline, despite some of their advantages such as being cleaner and to some extent renewable. We address these objections in this paper. Topics discussed include the ""corn connection"" (which was theorized to be a cause of deforestation in the Amazonia), the rise of food prices due to ethanol production and the real possibilities of ethanol in reducing greenhouse gas emissions. It has been shown that such concerns are grossly exaggerated and that ethanol from sugarcane, as produced in Brazil, is the preferred option for the production of fuel not only in terms of cost but also as a favourable energy balance. Finally, the possibility of expanding ethanol production to other sugar-producing countries is also discussed. (C) 2008 Elsevier Ltd. All rights reserved.

Beta-binomial/Poisson regression models for repeated bivariate counts

We analyze data obtained from a study designed to evaluate training effects on the performance of certain motor activities of Parkinson`s disease patients. Maximum likelihood methods were used to fit beta-binomial/Poisson regression models tailored to evaluate the effects of training on the numbers of attempted and successful specified manual movements in 1 min periods, controlling for disease stage and use of the preferred hand. We extend models previously considered by other authors in univariate settings to account for the repeated measures nature of the data. The results suggest that the expected number of attempts and successes increase with training, except for patients with advanced stages of the disease using the non-preferred hand. Copyright (c) 2008 John Wiley & Sons, Ltd.

Ca(2+)-mediated thiolysis of peptide-resin linkage as an option for preparing protected peptide thioesters

A mild new procedure for preparing protected peptide thioesters, based oil Ca(2+)-assisted thiolysis of peptide-Kaiser oxime resin (KOR) linkage, is described. Ac-Ile-Ser(Bzl)-Asp(OcHx)-SR (Ac: acetyl; Bzl: benzyl; cHx: cyclohexyl), model peptide, was readily released from the resin by incubating the peptide-KOR at 60 degrees C in mixtures of DMF with n-butanethiol [R = (CH(2))(3)CH(3)] or ethyl 3-mercaptopropionate [R = (CH(2))(2)COOCHCH(3)] containing Ca(CH(3)COO)(2). After serine and aspartic acid side-chain deprotection under acid conditions, Ac-Ile-Ser-Asp-S(CH(2))(2)COOCH(2)CH(3) was successfully obtained with good quality and high yield. This type of C-terminal modified peptide may act as an excellent acyl donor in peptide segment condensation by the thioester method, native chemical ligation and enzymatic methods. (c) 2008 Elsevier Ltd. All rights reserved.