Practical modeling strategies for unbalanced longitudinal data analysis

In practice, data are often measured repeatedly on the same individual at several points in time. Main interest often relies in characterizing the way the response changes in time, and the predictors of that change. Marginal, mixed and transition are frequently considered to be the main models for continuous longitudinal data analysis. These approaches are proposed primarily for balanced longitudinal design. However, in clinic studies, data are usually not balanced and some restrictions are necessary in order to use these models. This paper was motivated by a data set related to longitudinal height measurements in children of HIV-infected mothers that was recorded at the university hospital of the Federal University in Minas Gerais, Brazil. This data set is severely unbalanced. The goal of this paper is to assess the application of continuous longitudinal models for the analysis of unbalanced data set.     

Computations of Signatures of Coherent Systems with Five Components

The signatures of coherent systems are useful tools to compute the system reliability functions, the system expected lifetimes and to compare different systems using stochastic orderings. It is well known that there exist 2, 5, and 20 different coherent systems with 2, 3, and 4 components, respectively. The signatures for these systems were given in Shaked and Suarez-Llorens (2003 Shaked , M. , Suarez-Llorens , A. ( 2003 ). On the comparison of reliability experiments based on the convolution order . Journal of the American Statistical Association 98 : 693 – 702 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). In this article, we obtain an algorithm to compute all the coherent systems with n components and their signatures. Using this algorithm we show that there exist 180 coherent systems with 5 components and we compute their signatures.     

Heteroscedastic Nonlinear Regression Models

A very general class of models for discrete data is introduced that includes log-linear, linear, and product models as special cases. Maximum likelihood equations are developed to yield a Fisher scoring algorithm for fitting the models to both complete and incomplete data. Two examples serve to underscore the usefulness of these models.     

A Framework for Skew-Probit Links in Binary Regression

We review several asymmetrical links for binary regression models and present a unified approach for two skew-probit links proposed in the literature. Moreover, under skew-probit link, conditions for the existence of the ML estimators and the posterior distribution under improper priors are established. The framework proposed here considers two sets of latent variables which are helpful to implement the Bayesian MCMC approach. A simulation study to criteria for models comparison is conducted and two applications are made. Using different Bayesian criteria we show that, for these data sets, the skew-probit links are better than alternative links proposed in the literature.     

Population dynamics ofTelenomus fariai (Hymenoptera: Scelionidae), a parasite of Chagas' disease vectors IX. Larval competition and population size regulation under laboratory conditions

Summary A series of experiments were carried out with the endophagous egg parasiteTelenomus fariai on its hostTriatoma phyllosoma pallidipennis to determine the possible role of intraspecific competition by the parasite progeny in population regulation of the parasite. Eight parasite densities (1, 3, 5, 10, 20, 30, 40, and 50 individuals per vial) were used, and the design of sequentially sacrificed replicates applied. Survivorship curves for each density indicated smaller number of progeny per host at higher densities, and the shapes of the curves suggested a relatively early mortality process.Morris' linear regression technique for determining within-generation density-dependence was used, and the results showed that only larval mortality could be identified as density dependent. The same technique applied within the larval stage proved that only mortality of larvae in their second, third, and fourth day of development were responsible for population regulation. The applicability of the technique, as well as the relevance of the results for natural population, is discussed.     

Use of approximate bayesian methods for the block and basu bivariate exponential distribution

Summary In this paper, we present a Bayesian analysis of the bivariate exponential distribution of Block and Basu (1974) assuming different prior densities for the parameters of the model and considering Laplace's method to obtain approximate marginal posterior and posterior moments of interest. We also find approximate Bayes estimators for the reliability of two-component systems at a specified timet ₀ considering series and parallel systems. We illustrate the proposed methodology with a generated data set.     

Correcting for Scale Perception Bias in Measuring Corruption: an Application to Chile and Spain

Corruption perceptions are commonly utilized as essential information to measure corruption across countries and regions. In this paper we consider the hypothesis that respondents to corruption perception questions utilize different response scales in their answers, i.e. for identical levels of corruption practices, subjects from one country could answer a different level of corruption perception than subjects from another country, based on socioeconomic characteristics. This hypothesis is investigated by utilizing the technique of anchoring vignettes with a sample of citizens in Spain and Chile. The results show that response scales are used differently across individuals in both countries, suggesting that the use of uncorrected measures of corruption perceptions could mislead some conclusions about the comparisons of the corruption levels between countries.     

Alternative definitions of bivariate equilibrium distributions

The concept of equilibrium distribution plays an important role in survival analysis, reliability and insurance studies. If we consider the problem of extending this concept to higher dimensions, we do not have a unique solution. In this paper, alternative definitions of bivariate equilibrium distributions are studied and proposed. The Navarro et al. (2006) proposal is considered and some new results are given. We continue with the Gupta and Sankaran's (1998) definition. Necessary and sufficient conditions for its existence are stated and a characterization theorem is given. As a third alternative, a new definition based on conditional specification is introduced and several results are obtained. Reliability properties of the different versions are studied.     

A goodness-of-fit test for overdispersed binomial (or multinomial) models

Overdispersion or extra variation is a common phenomenon that occurs when binomial (multinomial) data exhibit larger variances than that permitted by the binomial (multinomial) model. This arises when the data are clustered or when the assumption of independence is violated. Goodness-of-fit (GOF) tests available in the overdispersion literature have focused on testing for the presence of overdispersion in the data and hence they are not applicable for choosing between the several competing overdispersion models. In this paper, we consider a GOF test proposed by Neerchal and Morel [1998. Large cluster results for two parametric multinomial extra variation models. J. Amer. Statist. Assoc. 93(443), 1078–1087], and study its distributional properties and performance characteristics. This statistic is a direct analogue of the usual Pearson chi-squared statistic, but is also applicable when the clusters are not necessarily of the same size. As this test statistic is for testing model adequacy against the alternative that the model is not adequate, it is applicable in testing two competing overdispersion models.