Enrollment,Educational Expenditures and Work Among One-Parent Children in India

In this study, I examined the effect of single parenthood due to death, separation, divorce, or migration of spouse on educational inputs among school-age children in India. I used the nationally representative India Human Development Survey to study the implications of different types of parenthood on educational expenditure among children ages 6 to 11 and 12 to 18 years and work participation among the older age group. The study finds that the separated or divorced mothers on average spend less on education and older children of widows are more likely to work because of resource constraints associated with single parenthood. The results highlight the need for public policies that would support widows as well as separated or divorced mothers.     

A Bayesian test of independence in a two-way contingency table using surrogate sampling

We consider a Bayesian approach to the study of independence in a two-way contingency table which has been obtained from a two-stage cluster sampling design. If a procedure based on single-stage simple random sampling (rather than the appropriate cluster sampling) is used to test for independence, the p-value may be too small, resulting in a conclusion that the null hypothesis is false when it is, in fact, true. For many large complex surveys the Rao–Scott corrections to the standard chi-squared (or likelihood ratio) statistic provide appropriate inference. For smaller surveys, though, the Rao–Scott corrections may not be accurate, partly because the chi-squared test is inaccurate. In this paper, we use a hierarchical Bayesian model to convert the observed cluster samples to simple random samples. This provides surrogate samples which can be used to derive the distribution of the Bayes factor. We demonstrate the utility of our procedure using an example and also provide a simulation study which establishes our methodology as a viable alternative to the Rao–Scott approximations for relatively small two-stage cluster samples. We also show the additional insight gained by displaying the distribution of the Bayes factor rather than simply relying on a summary of the distribution.     

Adaptive nonparametric tests for the two-sample scale problem under symmetry

The present paper considers two-sample tests for scale problem under symmetry without any assumption regarding the equality of medians. Two adaptive procedures are proposed—one is probabilistic while the other is deterministic. The proposed probabilistic approach is shown, by simulation studies, to maintain its significance level for various symmetric distributions and is found to be superior to the other existing competitors in terms of both robustness of size and power. Both the adaptive procedures are illustrated by using a real data. Some relevant asymptotic properties are also discussed.     

Exact sampling of the unobserved covariates in Bayesian spline models for measurement error problems

In truncated polynomial spline or B-spline models where the covariates are measured with error, a fully Bayesian approach to model fitting requires the covariates and model parameters to be sampled at every Markov chain Monte Carlo iteration. Sampling the unobserved covariates poses a major computational problem and usually Gibbs sampling is not possible. This forces the practitioner to use a Metropolis–Hastings step which might suffer from unacceptable performance due to poor mixing and might require careful tuning. In this article we show for the cases of truncated polynomial spline or B-spline models of degree equal to one, the complete conditional distribution of the covariates measured with error is available explicitly as a mixture of double-truncated normals, thereby enabling a Gibbs sampling scheme. We demonstrate via a simulation study that our technique performs favorably in terms of computational efficiency and statistical performance. Our results indicate up to 62 and 54 % increase in mean integrated squared error efficiency when compared to existing alternatives while using truncated polynomial splines and B-splines respectively. Furthermore, there is evidence that the gain in efficiency increases with the measurement error variance, indicating the proposed method is a particularly valuable tool for challenging applications that present high measurement error. We conclude with a demonstration on a nutritional epidemiology data set from the NIH-AARP study and by pointing out some possible extensions of the current work.     

Reflexive Development: A Model for Helping Social Workers Contribute to a Sustainable Global Future

It is difficult for many social work students to grasp the importance they and their traditional client base play in global environmental issues. International development generally focuses on supporting human development through the development of natural resources. However, increased human consumption everywhere in the world is disrupting the global system upon which all life depends. Continued Western consumption habits are simply unsustainable. It is therefore incumbent that any increase in consumption, even in the ‘developing’ world, be considered in terms of global environmental sustainability; change must also occur within the developed world. To address this problem, reflexive processes that support transnational analysis and action must be developed. This paper suggests classroom activities that help students analyze and problem solve around this process of Reflexive Development.