Child Rights Practice among the Indigenous Communities in Bangladesh

The objective of this article was to explore the practice of child rights among the indigenous communities of Bangladesh. We used a mixed method approach to collect data from four ethnic communities in the Bandarban District of the Chittagong Division in Bangladesh. We questioned children, parents, community members, local leaders, and service providers of those communities on a number of child rights issues, for example, child education, child labor, child recreation and culture, parents' guidance to children for capacity development, and access to child rights at home and in the community according to Convention on the Rights of the Child treaty. The results showed that while the community was aware of child rights, financial vulnerability and a lack of social support meant that these rights could not be upheld in practice. The paper urges improvement of social support, including income generation activities for indigenous communities.     

Random effects models for operational patient pathways

Patient flow modeling is a growing field of interest in health services research. Several techniques have been applied to model movement of patients within and between health-care facilities. However, individual patient experience during the delivery of care has always been overlooked. In this work, a random effects model is introduced to patient flow modeling and applied to a London Hospital Neonatal unit data. In particular, a random effects multinomial logit model is used to capture individual patient trajectories in the process of care with patient frailties modeled as random effects. Intuitively, both operational and clinical patient flow are modeled, the former being physical and the latter latent. Two variants of the model are proposed, one based on mere patient pathways and the other based on patient characteristics. Our technique could identify interesting pathways such as those that result in high probability of death (survival), pathways incurring the least (highest) cost of care or pathways with the least (highest) length of stay. Patient-specific discharge probabilities from the health care system could also be predicted. These are of interest to health-care managers in planning the scarce resources needed to run health-care institutions.     

Statistical Analysis of Marginal Count Failure Data

Manufacturers want to assess the quality andreliability of their products. Specifically, they want to knowthe exact number of failures from the sales transacted duringa particular month. Information available today is sometimesincomplete as many companies analyze their failure data simplycomparing sales for a total month from a particular departmentwith the total number of claims registered for that given month.This information—called marginal count data—is, thus,incomplete as it does not give the exact number of failures ofthe specific products that were sold in a particular month. Inthis paper we discuss nonparametric estimation of the mean numbersof failures for repairable products and the failure probabilitiesfor nonrepairable products. We present a nonhomogeneous Poissonprocess model for repairable products and a multinomial modeland its Poisson approximation for nonrepairable products. A numericalexample is given and a simulation is carried out to evaluatethe proposed methods of estimating failure probabilities undera number of possible situations.     

The Feminist “Quarantine” on Hijab: A Study of Its Two Mutually Exclusive Sets of Meanings

The discourse on feminism is sharply polarized between those who regard hijab as essentially debilitating and those who see it as an enabling tool for dignity, self-worth and freedom. This article will discuss both the negative and positive associations of hijab and point out ways it is used by Muslim women for liberatory ends. It will go against the grain of a common argument that hijab equates seclusion and constraints on women’s participation in public life hence it is inherently oppressive. I will argue that hijab can potentially be used for diametrically opposite purposes. While acknowledging the fact that the Islamic dress code for women can be misused by patriarchal power systems as well as by women themselves, I will put forth arguments against dismissive and uncritical criticism of hijab.     

Economic and social inclusion of person with disability and transgender through skills development program of BRAC: A qualitative study

This article is based on the Skills Training for Advancing Resources (STAR) project for the youth initiative of the Bangladesh Rural Advancement Committee (BRAC) in Bangladesh. The objective was to explore the consequences of social and economic inclusion of this project for the persons with disability (PWDs) and transgender (TG) youth people. The research focused on how inclusive programmatic interventions created multidimensional impacts among the “marginalized” and “excluded” PWD and TG youths at the grassroots level. This study adopted a qualitative approach where in-depth case interviews and observation were applied for data collection. PWD and TG graduates, master craft persons (MCPs), employers, and program staff members were the participants in this study. Results found that PWD and TG youths faced vulnerabilities and social stigma in their lives and livelihood trajectories due to their physical inability and low level of social dignity. The STAR project has a certain level of contribution to the livelihoods of PWD and TG people, where these helped them to gain their social, cultural, and economic capital. Findings would be an important guideline for policymakers, NGO managers, and human rights workers.     

Visiting migrants: An introduction

This paper offers an overview of the origins and dynamics of the concept of migrant visits and introduces the key contributions of the special issue. We highlight the significance of visits that criss-cross many forms of migration and centre on these visits’ bilateral and multilateral nature. Furthermore, we emphasize emotional, sensory and bodily implications, which almost always shape encounters between migrants and others in such visits. The papers of this special issue contribute to a broad interdisciplinary agenda highlighting familial ties, networks and transnational spaces at the core of migration and mobility scholarship. Together, we offer new perspectives on the multidirectionality of visits and the role of relationships which drive, connect and diversify forms of migration and are facilitated by broader developments in technology, tourism and diasporic practices.     

Patient-specific dose finding in phase I clinical trials

This article proposes an extension of the continual reassessment method to determine the maximum tolerated dose (MTD) in the presence of patients' heterogeneity in phase I clinical trials. To start with a simple case, we consider the covariate as a binary variable representing two groups of patients. A logistic regression model is used to establish the dose–response relationship and the design is based on the Bayesian framework. Simulation studies for six plausible dose–response scenarios show that the proposed design is likely to determine the MTD more accurately than the design that does not take covariate into consideration.     

Stepwise local influence in generalized autoregressive conditional heteroskedasticity models

Detection of outliers or influential observations is an important work in statistical modeling, especially for the correlated time series data. In this paper we propose a new procedure to detect patch of influential observations in the generalized autoregressive conditional heteroskedasticity (GARCH) model. Firstly we compare the performance of innovative perturbation scheme, additive perturbation scheme and data perturbation scheme in local influence analysis. We find that the innovative perturbation scheme give better result than other two schemes although this perturbation scheme may suffer from masking effects. Then we use the stepwise local influence method under innovative perturbation scheme to detect patch of influential observations and uncover the masking effects. The simulated studies show that the new technique can successfully detect a patch of influential observations or outliers under innovative perturbation scheme. The analysis based on simulation studies and two real data sets show that the stepwise local influence method under innovative perturbation scheme is efficient for detecting multiple influential observations and dealing with masking effects in the GARCH model.     

A speciation-based bilevel niching method for multimodal truss design problems

Truss design is a well-known structural optimization problem that has important practical applications in various fields. Truss design problems are typically multimodal by nature, meaning that it offers multiple optimal solutions concerning the topology (combinatorial optimization problem) and/or sizes (continuous optimization problem) of the members, but they are evaluated to have similar or equally good objective function values. From a practical standpoint, it is desirable to find as many alternative designs as possible, rather than finding a single design, as often practiced. Several techniques based on classical and metaheuristic optimization methods have been developed for simultaneous optimization of topology and size of a truss. However, all these methods unable to find multiple topologies and their corresponding size solutions in a single run. A few metaheuristics incorporating niching techniques have been developed for finding multiple topologies for the truss design problem, but these studies ignored the fact that for each known topology, multiple design solutions in terms of size can be found. To address this issue, this paper proposes a bi-level truss formulation and subsequently a speciation-based bilevel niching method (BiL-NM) using such a formulation. The BiL-NM consists of a modified SPSO niching method which is robust to find multiple topologies and a canonical PSO for their corresponding size solutions. Extensive empirical studies are carried out to analyze the accuracy, robustness, and efficiency of the BiL-NM. The results confirm that the proposed BiL-NM is superior in all these three aspects over the state-of-the-art methods on several low to high-dimensional truss design problems.

     

Key considerations for choosing a statistical method to deal with incomplete treatment adherence in pragmatic trials

Pragmatic trials offer practical means of obtaining real-world evidence to help improve decision-making in comparative effectiveness settings. Unfortunately, incomplete adherence is a common problem in pragmatic trials. The commonly used methods in randomized control trials often cannot handle the added complexity imposed by incomplete adherence, resulting in biased estimates. Several naive methods and advanced causal inference methods (e.g., inverse probability weighting and instrumental variable-based approaches) have been used in the literature to deal with incomplete adherence. Practitioners and applied researchers are often confused about which method to consider under a given setting. This current work is aimed to review commonly used statistical methods to deal with non-adherence along with their key assumptions, advantages, and limitations, with a particular focus on pragmatic trials. We have listed the applicable settings for these methods and provided a summary of available software. All methods were applied to two hypothetical datasets to demonstrate how these methods perform in a given scenario, along with the R codes. The key considerations include the type of intervention strategy (point treatment settings, where treatment is administered only once versus sustained treatment settings, where treatment has to be continued over time) and availability of data (e.g., the extent of measured or unmeasured covariates that are associated with adherence, dependent confounding impacted by past treatment, and potential violation of assumptions). This study will guide practitioners and applied researchers to use the appropriate statistical method to address incomplete adherence in pragmatic trial settings for both the point and sustained treatment strategies.