Bayesian and likelihood-based inference for the bivariate normal correlation coefficient

The paper develops some objective priors for correlation coefficient of the bivariate normal distribution. The criterion used is the asymptotic matching of coverage probabilities of Bayesian credible intervals with the corresponding frequentist coverage probabilities. The paper uses various matching criteria, namely, quantile matching, highest posterior density matching, and matching via inversion of test statistics. Each matching criterion leads to a different prior for the parameter of interest. We evaluate their performance by comparing credible intervals through simulation studies. In addition, inference through several likelihood-based methods have been discussed.     

Constrained Bayes and empirical Bayes estimation under random effects normal ANOVA model with balanced loss function

The paper develops constrained Bayes and empirical Bayes estimators in the random effects ANOVA model under balanced loss functions. In the balanced normal–normal model, estimators of the Bayes risks of the constrained Bayes and constrained empirical Bayes estimators are provided which are correct asymptotically up to O(m^-1)$\mathrm{O}(m^{-1})$, that is the remainder term is o(m^-1)$\mathrm{o}(m^{-1})$, m$m$ denoting the number of strata.     

Cox regression analysis in presence of collinearity: an application to assessment of health risks associated with occupational radiation exposure

This paper considers the analysis of time to event data in the presence of collinearity between covariates. In linear and logistic regression models, the ridge regression estimator has been applied as an alternative to the maximum likelihood estimator in the presence of collinearity. The advantage of the ridge regression estimator over the usual maximum likelihood estimator is that the former often has a smaller total mean square error and is thus more precise. In this paper, we generalized this approach for addressing collinearity to the Cox proportional hazards model. Simulation studies were conducted to evaluate the performance of the ridge regression estimator. Our approach was motivated by an occupational radiation study conducted at Oak Ridge National Laboratory to evaluate health risks associated with occupational radiation exposure in which the exposure tends to be correlated with possible confounders such as years of exposure and attained age. We applied the proposed methods to this study to evaluate the association of radiation exposure with all-cause mortality.     

A stratified estimation of a sensitive character by using geometric distribution

Abstract

In this paper, we consider the estimation of a sensitive character when the population is consisted of several strata; this is undertaken by applying Niharika et al.’s model which is using geometric distribution as a randomization device. A sensitive parameter is estimated for the case in which stratum size is known, and proportional and optimum allocation methods are taken into account. We extended the Niharika et al.’s model to the case of an unknown stratum size; a sensitive parameter is estimated by applying stratified double sampling to the Niharika et al.’s model. Finally, the efficiency of the proposed model is compared with that of Niharika et al. in terms of the estimator variance.     

Compassion Satisfaction Among Social Work Practitioners: The Role of Work–Life Balance

Abstract

Previous research has established that social work practitioners are especially vulnerable to work-related psychological distress and burnout due to the high-stress nature of the profession, yet less research has focused on examining factors are associated with social worker retention. Emerging research on compassion satisfaction suggests that this factor could mitigate professional burnout, yet there is a gap in research focusing explicitly on examining compassion satisfaction among social workers. To address this gap in knowledge, this quantitative study collected survey data on practicing social workers who were alumni from a large southeastern university (n?=?120) to examine individual and organizational factors associated with compassion satisfaction. Multiple regression analyses revealed that higher levels of emotional intelligence, perceived work autonomy, and perceived work–life balance were associated with an increase in compassion satisfaction among experienced, licensed social work practitioners. Findings have implications for how social work employers can promote compassion satisfaction through cultivating emotional intelligence among practitioners, allowing social workers autonomy in decision making, and providing supportive work environments. Recommended directions for future research include longitudinal studies with large sample sizes that expound research on compassion satisfaction by examining the role of additional factors, such as client population, job role characteristics, and supervisor support.     

Behind the Rhetoric of Community Development: How is it perceived and practiced?

State and local governments in Western Australia increasingly identify ‘community development’ as a key approach for the delivery of community services. In this paper I explore how the concept of community development is understood and practiced by workers in the context of government community services. While definitions are most often presented as a universally understood approach, my key argument is, that there are instead, community development ‘discourses’ that are variously applied to diverse situations. Foucauldian notions of discourse and power are used to propose that, while there may be core and recognisable traits found within the language of community development, in any given situation these combine with a number of variables (most notably stemming from the organization responsible for community services) to form a ‘situated’ community development ‘discourse’.     

To what extent does breastfeeding explain Birth-interval effects on early childhood mortality?

This article shows that in Nepal breastfeeding almost completely explains the effects of following birth interval on childhood mortality during the first 18 months of age and partially explains the effect of following birth interval on childhood mortality between 18 and 60 months of age. Breastfeeding does not explain the effect of preceding birth interval on childhood mortality. The analysis is based on application of hazard models to data from the 1976 Nepal Fertility Survey.