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.

Water quality assessment of Toledo River and determination of metal concentrations by using SR-TXRF technique

The region of Toledo River, Parana, Brazil is characterized by intense anthropogenic activities. Hence, metal concentrations and physical-chemical parameters of Toledo River water were determined in order to complete an environmental evaluation catalog. Samples were collected monthly during one year period at seven different sites from the source down the river mouth, physical-chemical variables were analyzed, and major metallic ions were measured. Metal analysis was performed by using the synchrotron radiation total reflection X-ray fluorescence technique. A statistical analysis was applied to evaluate the reliability of experimental data. The analysis of obtained results have shown that a strong correlation between physical-chemical parameters existed among sites 1 and 7, suggesting that organic pollutants were mainly responsible for decreasing the Toledo River water quality.