Competing risks model for clustered data based on the subdistribution hazards with spatial random effects

In some applications, the clustered survival data are arranged spatially such as clinical centers or geographical regions. Incorporating spatial variation in these data not only can improve the accuracy and efficiency of the parameter estimation, but it also investigates the spatial patterns of survivorship for identifying high-risk areas. Competing risks in survival data concern a situation where there is more than one cause of failure, but only the occurrence of the first one is observable. In this paper, we considered Bayesian subdistribution hazard regression models with spatial random effects for the clustered HIV/AIDS data. An intrinsic conditional autoregressive (ICAR) distribution was employed to model the areal spatial random effects. Comparison among competing models was performed by the deviance information criterion. We illustrated the gains of our model through application to the HIV/AIDS data and the simulation studies.KEYWORDS: Competing risks, subdistribution hazard, cumulative incidence function, spatial random effect, Markov chain Monte Carlo     

Kiefer–Wolfowitz algorithm under quasi-associated random errors

In this article, we study the algorithm of Kiefer–Wolfowitz underquasi-associated random errors. We establish the complete convergence and obtain an exponential bound. Additionally, we build a confidence interval for the minimum. Numerical examples are sketched out to confirm the theoretical results and show the accuracy of the algorithm.     

Women’s Decision to Divorce in Light of Failure in Marital Status and Dignity

In Iranian society, divorce, as an instability index of family, has been on the increase over the last decade. In particular, this separation is fraught with considerable difficulties for wives with children. The overall aim of this study is to investigate the nature of the process of deciding to separate by the divorced women despite having children. Resting on the grounded theory method, this study was conducted among 20 divorced women with children in the city of Tehran. The findings show that having a child is not a determining factor for the women to remain married; rather, what determines the separation of women with children is experiencing a status loss within their marital life, an experience that originates from losing her status after a woman has gotten married. Of course, women’s agency within the domain of family disintegration happens when they have the ability to overcome social fears and also have economic support. Through this course of events, although children are of enormous importance for the mothers, they are temporarily neglected while the mothers, for a short period, think primarily of saving themselves. Making their final decision to get separated leads to reactivating the role of their children; then, the mothers proceed to make the optimal decision.     

Some bounds related to Harris family of distributions

As a lifetime distribution, Harris family of distributions are applied to the lifetime of a series system with random number of components. In this paper, properties of various ageing classes of mixtures of Harris family of distributions, where the tilt parameter of a Harris distribution is taken as a random variable, are studied. We obtain an upper bound for maximum error in evaluating its reliability function. Two bounds are also presented for survival function and expectation of the mixed Harris family. We also provide some interesting bounds for its residual survival function. Our results generalize several previous findings in this connection. Some illustrative examples are also provided.     

Sexual Dynamics of Iranian Remarried Women in Blended Families: A Qualitative Study on Remarried Women’s Life

Despite the indispensable importance of the sexual relationship to the family dynamics, there has never been a study on remarried Iranian women in blended families. For the purpose of this study, 52 divorced women, who married for the second time, were interviewed. The data were codified line by line using thematic content analysis. Six main themes were identified from the interviews: (a) intrapersonal effects, (b) interpersonal effects, (c) attachment-based sexual relationships, (d) a new start, (e) family-related stress, and (f) pregnancy-related issues. Many of these women reported they were still thinking about their previous relationship and were influenced especially by how their ex-husband evaluated their body image. These findings presented a relatively clear image of the impact of remarriage on the sexuality of Iranian remarried women in blended families. These findings suffer from some constraints, such as generalizing of the data due to the small sample size.     

Consistency of stochastic approximation algorithm with quasi-associated random errors

ABSTRACT

Many mathematical and physical problems are led to find a root of a real function f. This kind of equation is an inverse problem and it is difficult to solve it. Especially in engineering sciences, the analytical expression of the function f is unknown to the experimenter, but it can be measured at each point x_k with M(x_k) as expected value and induced error ξ_k. The aim is to approximate the unique root θ under some assumptions on the function f and errors ξ_k. We use a stochastic approximation algorithm that constructs a sequence (x_k)_{k ? 1}. We establish the almost complete convergence of the sequence (x_k)_k to the exact root θ by considering the errors (ξ_k)_k quasi-associated and we illustrate the method by numerical examples to show its efficiency.     

Bayesian alignment of proteins via Delaunay tetrahedralization

An active area of research in bioinformatics is finding structural similarity of proteins by alignment. Among many methods, the popular one is to find the similarity based on statistical features. This method involves gathering information from the complex biomolecule structure and obtaining the best alignment by maximizing the number of matched features. In this paper, after reviewing statistical models for matching the structural biomolecule, it is shown that local alignment based on the Delaunay tetrahedralization (DT) can be used for Bayesian alignment of proteins. In this method, we use DT to add a priori structural information of protein in the Bayesian methodology. We demonstrate that this method shows advantages over competing methods in achieving a global alignment of proteins, accelerating the convergence rate and improving the parameter estimates.     

Perceived Cultural Distance in Healthcare in Immigrant Intercultural Medical Encounters

This article responds to the paucity of empirical research on the impact of patient-provider ethno-cultural distance and providers' cultural competence on the quality of healthcare service in migrant intercultural medical encounters in Australia. A cross-sectional study was conducted with 447 patients, consisting of 195 Caucasian and 252 non-Caucasian patients from six outpatient clinics in New South Wales, Australia. Structural equation modelling was used for data analysis. The findings demonstrated that cultural distance is an influential factor in perceived quality of outpatient care. Caucasian and non-Caucasian patients' perception of cultural distance between their physicians and themselves affected their service quality ratings of their physicians' professionalism, empathy and expertise. This is the first study on healthcare service quality in outpatient clinics in Australia for Caucasian and non-Caucasian patients. Policy implications suggest intervention strategies and the need for cultural competence education in medical and health curricula in medical schools and clinical practices.     

Spatio-temporal Trend Analysis of Spring Arrival Data for Migratory Birds

There is increasing interest in spatio-temporal analysis of environmental and ecological responses to changes in the climate due to the recent concerns about climate change. In this work, we propose a spatio-temporal modeling framework for analyzing environmental and ecological data while accounting for spatial and temporal structure, as well as climate effects. As an example, we consider data on bird migration in the United States and analyze the spring arrival dates of Purple Martins between historical data (1905–1940) from the North American Bird Phenology Program and recent data (2001–2010) from the Purple Martin Conservation Association. The proposed approach allows researchers to compare mean arrival dates while accounting for spatial and temporal variability. Our results for Purple Martins showed statistically significant earlier spring arrivals in parts of United States over the recent years. The proposed approach provides a useful tool for statistical analysis of spatio-temporal data related to studies of climate change.