Standard Exponential Cure Rate Model with Noninformative or Informative Uniform-Exponential Censoring

In survival data analysis it is frequent the occurrence of a significant amount of censoring to the right indicating that there may be a proportion of individuals in the study for which the event of interest will never happen. This fact is not considered by the ordinary survival theory. Consequently, the survival models with a cure fraction have been receiving a lot of attention in the recent years. In this article, we consider the standard mixture cure rate model where a fraction p ₀ of the population is of individuals cured or immune and the remaining 1 ? p ₀ are not cured. We assume an exponential distribution for the survival time and an uniform-exponential for the censoring time. In a simulation study, the impact caused by the informative uniform-exponential censoring on the coverage probabilities and lengths of asymptotic confidence intervals is analyzed by using the Fisher information and observed information matrices.     

A bayesian method for inferring the degree fo dependence for a positively quadrant dependent distribution

A Bayesian method for making inferences on the degree of dependence for a positively quadrant dependent distribution is developed. This method is based on a parametric model, where the parameter measures the degree of association. The parametric model is a natural simplification of the original one: it is a mixture of the two extreme cases corresponding to independence and positive extremal dependence.     

Rational Economic Data Revisions

The efficient handling of provisional economic time series data is considered. Procedures are justified in terms of a testable hypothesis regarding the nature of data revisions. The hypothesis leads to explicit and practical variance expressions for measurement errors. Testing and estimation issues are dealt with. An efficient dual filter is developed for recursive signal estimation. Techniques are applied to the Canadian index of production data.     

Health-related determinants of perceived quality of life: a comparison between first-year university students and their working peers

This study compares aspects of the health-related behaviors and working life of first-year university students with those of their working counterparts and assesses the roles of these aspects as predictors of each groups' perceived quality of life (QoL). Subjects were taken from two cross-sectional data sets (a student survey and a population survey) from the Swedish central-western region of Osterg?tland. Male and female respondents aged 20-35 years were extracted and comparison were made considering in turn socio-demographic characteristics, health-related behaviors, exposure to abusive events at work and perceived QoL. University students smoked and used oral snuff in smaller proportions, they were not as frequent drinkers as their working counterparts, but they tended to drink more when they did drink. Threats and violence were less prevalent among students, but sexual harassment, were almost as common. The strongest predictors of perceived QoL for both groups are expected and former perceived QoL, followed by current self-rated health.     

Sample size for estimating a binomial proportion: comparison of different methods

The poor performance of the Wald method for constructing confidence intervals (CIs) for a binomial proportion has been demonstrated in a vast literature. The related problem of sample size determination needs to be updated and comparative studies are essential to understanding the performance of alternative methods. In this paper, the sample size is obtained for the Clopper–Pearson, Bayesian (Uniform and Jeffreys priors), Wilson, Agresti–Coull, Anscombe, and Wald methods. Two two-step procedures are used: one based on the expected length (EL) of the CI and another one on its first-order approximation. In the first step, all possible solutions that satisfy the optimal criterion are obtained. In the second step, a single solution is proposed according to a new criterion (e.g. highest coverage probability (CP)). In practice, it is expected a sample size reduction, therefore, we explore the behavior of the methods admitting 30% and 50% of losses. For all the methods, the ELs are inflated, as expected, but the coverage probabilities remain close to the original target (with few exceptions). It is not easy to suggest a method that is optimal throughout the range (0, 1) for p. Depending on whether the goal is to achieve CP approximately or above the nominal level different recommendations are made.