Improved Predictive Inference for Responses Based on Location Parameter Median from the Rayleigh Model Given a Doubly Censored Sample

The purpose of this article is to investigate the predictive inference for responses from the location parameter mean as well as from the median given a doubly censored sample from the two-parameter Rayleigh model. The predictive results by Khan et al. (2010 Khan , H. M. R. , Provost , S. B. , Ashima , S. ( 2010 ). Predictive Inference from a Two-Parameter Rayleigh Life Model Given a Doubly Censored Sample . Commun. Statist. Theor. Meth. 39 ( 7 ): 1237 – 1246 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) are used to obtain the predictive inference for responses from the median, where Khan et al. (2010 Khan , H. M. R. , Provost , S. B. , Ashima , S. ( 2010 ). Predictive Inference from a Two-Parameter Rayleigh Life Model Given a Doubly Censored Sample . Commun. Statist. Theor. Meth. 39 ( 7 ): 1237 – 1246 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) obtained the future estimates from the mean. A numerical example representing 66 liver cancer patients is used for predictive analysis. It is concluded that the predictive inference from the median gives precise results as compared with the location parameter mean.     

Determining the optimal allocation of testing resource for modular software system using dynamic programming

Abstract

Reliability is a major concern in the process of software development because unreliable software can cause failure in the computer system that can be hazardous. A way to enhance the reliability of software is to detect and remove the faults during the testing phase, which begins with module testing wherein modules are tested independently to remove a substantial number of faults within a limited resource. Therefore, the available resource must be allocated among the modules in such a way that the number of faults is removed as much as possible from each of the modules to achieve higher software reliability. In this article, we discuss the problem of optimal resource allocation of the testing resource for a modular software system, which maximizes the number of faults removed subject to the conditions that the amount of testing-effort is fixed, a certain percentage of faults is to be removed and a desired level of reliability is to be achieved. The problem is formulated as a non linear programming problem (NLPP), which is modeled by the inflection S-shaped software reliability growth models (SRGM) based on a non homogeneous Poisson process (NHPP) which incorporates the exponentiated Weibull (EW) testing-effort functions. A solution procedure is then developed using a dynamic programming technique to solve the NLPP. Furthermore, three special cases of optimum resource allocations are also discussed. Finally, numerical examples using three sets of software failure data are presented to illustrate the procedure developed and to validate the performance of the strategies proposed in this article. Experimental results indicate that the proposed strategies may be helpful to software project managers for making the best decisions in allocating the testing resource. In addition, the results are compared with those of Kapur et al. (2004), Huang and Lyu (2005), and Jha et al. (2010) that are available in the literature to deal the similar problems addressed in this article. It reveals that the proposed dynamic programming method for the testing-resource allocation problem yields a gain in efficiency over other methods.     

Improved estimation of the mean vector for student-t model

Improved James-Stein type estimation of the mean vector μ of a multovaroate Student-t population of dimension p with ν degrees of freedom is considered. In addition to the sample data, uncertain prior information on the value of the mean vector, in the form of a null hypothesis, is used for the estiamtion. The usual maximum liklihood estimator((mle) of μ is obtained and a test statistic for testing H₀:μ=μ₀ is derived. Based on the mle of μ and the tes statistic the preliminary test estimator (PTE), Stein-type shrinkage estimator (SE) and positive-rule shrinkage esiimator (PRSE) are defined. The bias and the quadratic risk of the estimators are evaiuated. The relative performances of the estimators are mvestigated by analyzing the risks under different condltlons It is observed that the FRSE dommates over he other three estimators, regardless of the vaiidity of the null hypothesis and the value ν.     

Are rural–urban migrants living in urban slums more vulnerable in terms of housing,health knowledge,smoking, mental health and general health?

The magnitude of rural–urban migration in Bangladesh is increasing. Rapid urbanisation and a growing number of slums (dominated by migrants) pose many challenges to health. To our knowledge, studies regarding internal migration and health are scarce and results are mixed. Therefore, we compared several aspects, namely: housing, health knowledge, smoking, mental and general health, for three groups of migrants, designated urban natives/urban to urban migrants (UN/UU), rural to urban migrants (RU) and rural natives/rural to rural migrants (RN/RR). Results based on a sample of 5,136 adults indicated that the majority of respondents were less than 50 years old, female, married and uneducated. The percentages of UN/UU, RU and RN/RR migrants were 9.6, 69.2 and 21.3, respectively. As both bivariable and multivariable analyses indicated greater vulnerability among RU migrants in terms of the above‐mentioned aspects, this particular group deserves more attention from policy‐makers and other stakeholders. Some implications are also discussed. Key Practitioner Message: ● This study provides information regarding internal migration and explains push–pull factors in Bangladesh; ● It provides evidence regarding greater vulnerability in terms of health and other determinants among rural–urban migrants living in Dhaka slums; ● Lastly, the study justifies the importance of intervention strategies targeting poor migrants in urban slums in developing countries.     

Sexual and reproductive health knowledge and information-seeking behavior among middle eastern female university students: a systematic review

Objectives: The objective of this study was to collate the level of sexual and reproductive health knowledge, awareness, attitudes, and behavior among female university students, in addition to identifying their sources of information in Middle Eastern and North African countries. Methods: A systematic review was conducted with a search in Medline, EMBASE, Web of Knowledge, PsycINFO, and CINAHL from inception to February 2013. Included were studies in any language describing sexual and reproductive health knowledge and attitudes among female university students. Results: Nine studies were included, and all were cross-sectional surveys. There was a general lack of knowledge of sexual and reproductive health. The highest knowledge levels reported were for HIV. Conclusions: There are deficiencies in sexual and reproductive health knowledge and behavior in Middle Eastern and North African countries. Studies are needed to evaluate how to provide culturally sensitive sexual and reproductive health information.     

Designing stratified sampling in economic and business surveys

In most economic and business surveys, the target variables (e.g. turnover of enterprises, income of households, etc.) commonly resemble skewed distributions with many small and few large units. In such surveys, if a stratified sampling technique is used as a method of sampling and estimation, the convenient way of stratification such as the use of demographical variables (e.g. gender, socioeconomic class, geographical region, religion, ethnicity, etc.) or other natural criteria, which is widely practiced in economic surveys, may fail to form homogeneous strata and is not much useful in order to increase the precision of the estimates of variables of interest. In this paper, a stratified sampling design for economic surveys based on auxiliary information has been developed, which can be used for constructing optimum stratification and determining optimum sample allocation to maximize the precision in estimate.     

The challenges and coping strategies of single mothers caring for children with special needs: Experiences from Kashmir,India

Families play a significant role in the development of their children. Nearly 16% of children in the industrialized world live in single-parent households, which are mostly comprised of single mothers. Although motherhood is the most beautiful feeling a woman cherishes, this experience can be challenging when the woman has to raise their special-needs child on her own, without the support of her spouse or partner. This study aims to understand the challenges and coping strategies of single mothers while raising their special-needs children. To this end, in-depth case interviews were conducted with three single mothers selected purposively from the Srinagar area in Kashmir, India. The results revealed that multiple roles and responsibilities had an adverse effect on the psychological well-being of single mothers who had to deal with the financial burden of caring for their child's condition, including expenses for doctor visits, special therapies and medication, among other. In addition, they had to experience the social pressure and stigmatization attached to being a single mother. The most widely employed coping strategies include support from family and friends, religious faith, and self-coping. The study recommends the creation of welfare packages like free counseling, stipend support, inclusive education, free medical treatment, and therapies for Children with Special Needs (CWSNs) and their mothers.     

Working with Stepfamilies

Stepfamilies are complex family systems that warrant a specific model to guide therapy practice. Once a stepfamily has formed it's easy to overlook the lack of an attachment history that is commonly embedded in a biologically connected nuclear family. This can result in stepparents picking up parental responsibility for their stepchildren, which often may not go well. This paper highlights the need for clarity concerning the different levels of connection within a stepfamily, and the importance of avoiding ‘nuclear family‐style’ solutions and assumed attachments. This is especially important in the early stages of the relationship when everyone is adjusting to changing circumstances, which is often a time when issues of loyalty and betrayal fuel many of the actions taken. A range of family therapy techniques can be helpfully adapted to working with stepfamilies, especially as relationships with children often bring them to therapy. In particular, therapists can utilise ideas from structural family therapy to help guide the stepfamily to navigate the complexities of everyday life.     

A GQL estimation approach for analysing non-stationary over-dispersed BINAR(1) time series

This paper proposes a generalized quasi-likelihood (GQL) function for estimating the vector of regression and over-dispersion effects for the respective series in the bivariate integer-valued autoregressive process of order 1 (BINAR(1)) with Negative Binomial (NB) marginals. The auto-covariance function in the proposed GQL is computed using some ‘robust’ working structures. As for the BINAR(1) process, the inter-relation between the series is induced mainly by the correlated NB innovations that are subject to different levels of over-dispersion. The performance of the GQL approach is tested via some Monte-Carlo simulations under different combination of over-dispersion together with low and high serial- and cross-correlation parameters. The model is also applied to analyse a real-life series of day and night accidents in Mauritius.