Home Environment and Its Relation with Quality of Life of Older People

In this cross-sectional study, we tested the relationship between sociophysical environment, quality of life (QOL), and perceived social support among elderly in Iran. The sample includes 128 participants recruited in the city of Shahrekord, Iran. We measured Evaluation of Older People Living Environment (EVOLVE); Control, Autonomy, Self-realization and Pleasure scale (CASP-19) and Multidimensional Scale of Perceived Social Support (MSPSS) tools respectively, through home-based observation and interview. A significant relationship was found between several domains of home environment, QOL, and perceived social support. The interaction effect of the home environment and gender in relation to QOL and perceived social support was statistically significant. Our results support that the home physical environment may not be considered a strong predictor of QOL among the Iranian elderly.     

Religiosity,Citizenship and Belonging: The Everyday Experiences of Young Australian Muslims

Abstract

Since 11 September 2001 Muslim Diasporas have emerged as objects of anxiety in Western societies. Underlying this (in)security-driven problematisation is the question of whether Muslims living in the West have the capacity to become fully active citizens while maintaining their religious beliefs, rituals and practices. This apprehension has prompted reactionary government programmes, particularly targeting young Muslims. Such responses fail to recognise the societal capacities that practising Muslims possess, including those informed by the ethical precepts of Islamic faith. This paper argues that it is timely to explore expressions of Islamic religiosity as they are grounded in everyday multicultural environments. The paper draws on survey data and interviews conducted with Muslims living in Melbourne, Australia. We take into consideration key variables of age and generation to highlight how young, practising Muslims enact citizenship through Islamic rituals and faith-based practices and traditions. The paper will draw from key findings to argue that these performances provide a foundation for exploring ways of ‘living’ together in a manner that privileges ethics central to Islamic faith traditions.     

Preservation properties of stochastic orders by transformation to the transmuted-G model

Abstract

The transmuted-G model is a useful technique to construct some new distributions by adding a parameter. This paper considers stochastic comparisons in the transmuted-G family with different parameters and different baseline distributions in the sense of the usual stochastic, shifted stochastic, proportional stochastic and shifted proportional stochastic orders. Also, we present a necessary and sufficient condition for existence of the moments of the transmuted-G model and then we obtain some bounds for the survival and aging intensity functions of the transmuted-G model conditioned on its parameter and its baseline distribution.     

INDETERMINACY AND VOLATILITY OF EXCHANGE RATES UNDER IMPERFECT CURRENCY SUBSTITUTION

We know that when currencies are perfect substitutes, exchange rates could become indeterminate. We show that even when currencies are less than perfect substitutes exchange rates could display volatility unrelated to economic fundamentals. With increases in currency substitution: (1) the exchange rate becomes more sensitive to changes in economic fundamentals, increasing its volatility; (2) the exchange rate could become indeterminate, and it is more likely to become so if governments pursue similar monetary policies; (3) currencies with high nominal interest rates would decline significantly and the exchange rate becomes more sensitive to changes in the supply of those currencies.     

Women’s Well-Being in Iran: Territorial Analysis Using a Multidimensional Approach

This paper employs a multidimensional index for assessing women’s well-being in Iranian provinces using demographic and health survey macro data. Besides economic status as a traditional dimension for objective well-being, other factors such as health, education, risk, and technology as well as self-reported life satisfaction and happiness (psychological well-being) have been included as non-material well-being dimensions. We found that the values of women’s well-being are distributed unequally across the provinces. Southern provinces demonstrate the worst performances and central provinces have the best. Generally, Iranian women are in poor condition in terms of economic variables (e.g. income and participation in the job market), psychological well-being (life satisfaction), HIV literacy, use of the internet, and access to mass media. On the other hand, in recent years, they have made significant progress in education (such as the rate of literacy, high school degree), and health (safe pregnancy care and nutritional supplements).     

Heavy or semi-heavy tail,that is the question

While there has been considerable research on the analysis of extreme values and outliers by using heavy-tailed distributions, little is known about the semi-heavy-tailed behaviors of data when there are a few suspicious outliers. To address the situation where data are skewed possessing semi-heavy tails, we introduce two new skewed distribution families of the hyperbolic secant with exciting properties. We extend the semi-heavy-tailedness property of data to a linear regression model. In particular, we investigate the asymptotic properties of the ML estimators of the regression parameters when the error term has a semi-heavy-tailed distribution. We conduct simulation studies comparing the ML estimators of the regression parameters under various assumptions for the distribution of the error term. We also provide three real examples to show the priority of the semi-heavy-tailedness of the error term comparing to heavy-tailedness. Online supplementary materials for this article are available. All the new proposed models in this work are implemented by the shs R package, which can be found on the GitHub webpage.     

A non-homogeneous skew-Gaussian Bayesian spatial model

In spatial statistics, models are often constructed based on some common, but possible restrictive assumptions for the underlying spatial process, including Gaussianity as well as stationarity and isotropy. However, these assumptions are frequently violated in applied problems. In order to simultaneously handle skewness and non-homogeneity (i.e., non-stationarity and anisotropy), we develop the fixed rank kriging model through the use of skew-normal distribution for its non-spatial latent variables. Our approach to spatial modeling is easy to implement and also provides a great flexibility in adjusting to skewed and large datasets with heterogeneous correlation structures. We adopt a Bayesian framework for our analysis, and describe a simple MCMC algorithm for sampling from the posterior distribution of the model parameters and performing spatial prediction. Through a simulation study, we demonstrate that the proposed model could detect departures from normality and, for illustration, we analyze a synthetic dataset of CO\(_2\) measurements. Finally, to deal with multivariate spatial data showing some degree of skewness, a multivariate extension of the model is also provided.