Prediction of disease status: A regressive model approach for repeated measures

In this paper, regressive models are proposed for modeling a sequence of transitions in longitudinal data. These models are employed to predict the future status of the outcome variable of the individuals on the basis of their underlying background characteristics or risk factors. The estimation of parameters and also estimates of conditional and unconditional probabilities are shown for repeated measures. The goodness of fit tests are extended in this paper on the basis of the deviance and the Hosmer–Lemeshow procedures and generalized to repeated measures. In addition, to measure the suitability of the proposed models for predicting the disease status, we have extended the ROC curve approach to repeated measures. The procedure is shown for the conditional models for any order as well as for the unconditional model, to predict the outcome at the end of the study. The test procedures are also suggested. For testing the differences between areas under the ROC curves in subsequent follow-ups, two different test procedures are employed, one of which is based on permutation test. In this paper, an unconditional model is proposed on the basis of conditional models for the disease progression of depression among the elderly population in the USA on the basis of the Health and Retirement Survey data collected longitudinally. The illustration shows that the disease progression observed conditionally can be employed to predict the outcome and the role of selected variables and the previous outcomes can be utilized for predictive purposes. The results show that the percentage of correct predictions of a disease is quite high and the measures of sensitivity and specificity are also reasonably impressive. The extended measures of area under the ROC curve show that the models provide a reasonably good fit in terms of predicting the disease status during a long period of time. This procedure will have extensive applications in the field of longitudinal data analysis where the objective is to obtain estimates of unconditional probabilities on the basis of series of conditional transitional models.     

Recalibration of the Grunow–Finke Assessment Tool to Improve Performance in Detecting Unnatural Epidemics

Successful identification of unnatural epidemics relies on a sensitive risk assessment tool designed for the differentiation between unnatural and natural epidemics. The Grunow–Finke tool (GFT), which has been the most widely used, however, has low sensitivity in such differentiation. We aimed to recalibrate the GFT and improve the performance in detection of unnatural epidemics. The comparator was the original GFT and its application in 11 historical outbreaks, including eight confirmed unnatural outbreaks and three natural outbreaks. Three steps were involved: (i) removing criteria, (ii) changing weighting factors, and (iii) adding and refining criteria. We created a series of alternative models to examine the changes on the parameter likelihood of unnatural outbreaks until we found a model that correctly identified all the unnatural outbreaks and natural ones. Finally, the recalibrated GFT was tested and validated with data from an unnatural and natural outbreak, respectively. A total of 238 models were tested. Through the removal of criteria, increasing or decreasing weighting factors of other criteria, adding a new criterion titled “special insights,” and setting a new threshold for likelihood, we increased the sensitivity of the GFT from 38% to 100%, and retained the specificity at 100% in detecting unnatural epidemics. Using test data from an unnatural and a natural outbreak, the recalibrated GFT correctly classified their etiology. The recalibrated GFT could be integrated into routine outbreak investigation by public health institutions and agencies responsible for biosecurity.     

Board size,director compensation,and firm transition across stock exchanges: evidence from Canada

Journal of Management and Governance - In this study, we examine the relationship between the role and compensation structure of non-executive directors when firms on the TSX Venture Exchange...     

Assessment of multidimensional poverty and effectiveness of microfinance-driven government and NGO projects in the rural Bangladesh

This paper has developed a multidimensional model usable in assessing economic, social, political and cultural dimensions of poverty by utilizing primary data collected from 78 villages in Bangladesh using a participatory approach. Employing the developed model, a comparative analysis has been performed between microfinance-driven government (GO) and NGO (non-government organization) projects to explore their relative effectiveness in enhancing wellbeing of the poor in rural Bangladesh. It is observed that GO agencies are more effective in enhancing ‘economic wellbeing’ of the poor, whereas NGOs are contributing more in the ‘social’ aspects of wellbeing. Findings also revealed that, as whole, GO agencies perform 42% better than NGOs in improving living standards of the rural poor which contradicts with the existing literature of poverty reduction projects in developing countries.     

Urban and peri-urban aquaculture as an immediate source of food fish: Perspectives of Dhaka City,Bangladesh

This paper describes the present status of aquaculture activities in Dhaka City and its surrounding areas including the system of fish marketing and distribution and environmental and socioeconomic issues. Dhaka City contains over 10 million people and is expanding day by day. Demand of fish in the last 10 years has increased as a result of increases in population and income levels. The annual per capita consumption of fish is reported to drop by 0.5 kg since 1985. The reason for this decline is increased prices and decreased supply of fish. Fish supply to the city comes from catch in the rivers-estuaries and floodlands of Dhaka district, neighboring districts, imports from other areas and aquaculture in surrounding areas of the city. Considerable quantities of fish are imported from India, Myanmar and Thailand. Seasonal patterns are common both in supply and consumption of fish. Along with traditional rural household aquaculture, in recent years, urban and peri-urban aquaculture has also been popular. Three broad types of aquaculture activities are found in and around Dhaka City; these are polyculture of carp in ponds, monoculture of catfishs in ponds, and pen and cage aquaculture in open waters. The carp includes both Indian major carp and Chinese carp and some minor carp. The catfish group includes mainly Thai pangas (Pangasius sutchi). Tilapia (Oreochromis niloticus) is also widely popular among the farmers. The technology used for aquaculture is improved extensive to semi-intensive. Increasing demand for fish in the city markets has encouraged the expansion of peri-urban aquaculture with a corresponding increase in the proportion of farmed fish in the markets.     

Optimal designs for minimising covariances among parameter estimators in a linear model

We construct approximate optimal designs for minimising absolute covariances between least‐squares estimators of the parameters (or linear functions of the parameters) of a linear model, thereby rendering relevant parameter estimators approximately uncorrelated with each other. In particular, we consider first the case of the covariance between two linear combinations. We also consider the case of two such covariances. For this we first set up a compound optimisation problem which we transform to one of maximising two functions of the design weights simultaneously. The approaches are formulated for a general regression model and are explored through some examples including one practical problem arising in chemistry.     

Birth-interval dynamics in rural Bangladesh and maternal weight

This article reports on the results of a study conducted in rural Bangladesh on the influence of maternal weight on the components of birth intervals, including gestation and intrauterine mortality, the duration of postpartum amenorrhea, and the duration of waiting time to conception (the menstrual interval). When biological factors (including maternal age, parity, and supplementation practices) and behavioral variables, including religion, education, and occupation, were controlled, maternal weight was found to be related to the risk of intrauterine mortality and to the probability of resuming menses in the postpartum period. The implications of these findings for policies and programs in developing countries are discussed.     

Underinvestment in a Profitable Technology: The Case of Seasonal Migration in Bangladesh

Hunger during pre‐harvest lean seasons is widespread in the agrarian areas of Asia and Sub‐Saharan Africa. We randomly assign an $8.50 incentive to households in rural Bangladesh to temporarily out‐migrate during the lean season. The incentive induces 22% of households to send a seasonal migrant, their consumption at the origin increases significantly, and treated households are 8–10 percentage points more likely to re‐migrate 1 and 3 years after the incentive is removed. These facts can be explained qualitatively by a model in which migration is risky, mitigating risk requires individual‐specific learning, and some migrants are sufficiently close to subsistence that failed migration is very costly. We document evidence consistent with this model using heterogeneity analysis and additional experimental variation, but calibrations with forward‐looking households that can save up to migrate suggest that it is difficult for the model to quantitatively match the data. We conclude with extensions to the model that could provide a better quantitative accounting of the behavior.     

Climate-related migration in rural Bangladesh: a behavioural model

Research into the climate change and migration nexus has often focussed solely on how people move in response to the impacts of variability and change in climate. This notion often ignores the nature of migration as a tried and tested livelihood choice amid a variety of socio-economic and environmental opportunities and limitations. This paper closely looks at the behavioural aspects of migration decision-making in Bangladesh in the context of changes in its economy, and, increasingly, exposure to the impacts of climate variability and change. We find that villagers in areas particularly affected by increasing climatic stresses and shocks are diversifying their traditional livelihood strategies by migrating. Environmental factors, including climatic stresses and shocks, often make such shifts even more necessary. Although the migrants’ primary motivation is better income, in effect, migration becomes an effective form of adaptation. Based on a qualitative study in three geographically distinct places of Bangladesh, we propose that migration is a socially acceptable behaviour that occurs in the context of perceived environmental change and climate variability. Migration decisions are mediated by a set of ‘behavioural factors’ that assesses the efficacy of different responses to opportunities and challenges, their socio-cultural acceptance and the ability to respond successfully. This understanding has policy relevance for climate change adaptation, in terms of both how migrants are perceived and how their movements are planned for.