Moving up the energy ladder: does socio-religious status matter?

This paper investigates the role played by socio-religious categories in determining primary cooking fuel choices among Indian households. We study this role in the broader context of climbing up the energy ladder. Our estimates based on a sample of 601,509 households and using multinomial probit regression suggest that socio-religious status along with economic status is critical in the choice of modern eco-friendly fuels. We find that belonging to a marginalized community in Hindu religion significantly dampens a households’ likelihood to move up the ladder when compared with upper caste households. While intra-religion differences among Hindu castes in terms of their probability of using modern fuels are wider, differences among Muslims appear smaller. Also, though Muslims perform worse than Hindu upper castes in terms of probability of using modern fuels they are much better off in comparison with other Hindu castes. Our results remain robust to alternative specifications and several robustness checks.

     

Reporting Errors in Siblings’ Survival Histories and Their Impact on Adult Mortality Estimates: Results From a Record Linkage Study in Senegal

Estimates of adult mortality in countries with limited vital registration (e.g., sub-Saharan Africa) are often derived from information about the survival of a respondent’s siblings. We evaluated the completeness and accuracy of such data through a record linkage study conducted in Bandafassi, located in southeastern Senegal. We linked at the individual level retrospective siblings’ survival histories (SSH) reported by female respondents (n = 268) to prospective mortality data and genealogies collected through a health and demographic surveillance system (HDSS). Respondents often reported inaccurate lists of siblings. Additions to these lists were uncommon, but omissions were frequent: respondents omitted 3.8 % of their live sisters, 9.1 % of their deceased sisters, and 16.6 % of their sisters who had migrated out of the DSS area. Respondents underestimated the age at death of the siblings they reported during the interview, particularly among siblings who had died at older ages (≥45 years). Restricting SSH data to person-years and events having occurred during a recent reference period reduced list errors but not age and date errors. Overall, SSH data led to a 20 % underestimate of ₄₅ q ₁₅ relative to HDSS data. Our study suggests new quality improvement strategies for SSH data and demonstrates the potential use of HDSS data for the validation of “unconventional” demographic techniques.     

The Design of a Knowledge-Based Decision Support System to Support the Information Analyst in Determining Requirements

Decision support system (DSS) researchers and designers continue to look for unstructured organizational tasks where there is a critical need for intelligent computer-based support. One such decision task is information requirements determination. Requirements determination is recognized as the most crucial phase of the systems development life cycle. Unfortunately, most methodologies and CASE tools focus only on how to specify the requirements once they are determined. There is very little computer support for the process of determining requirements. This paper discusses the conceptual design and development of a knowledge-based DSS to support information analysts in the critical decision task of determining requirements for the design of effective information systems. The expert modeling support system has the expertise to assist the analyst in studying the organization as a whole and in modeling the system under study in the context of the overall organization's goals and needs. The focus of the paper is on the problems associated with building the knowledge base component of the intelligent decision support system. A prototype implementation of the system is described.     

Application of digital human modeling and simulation for vision analysis of pilots in a jet aircraft: a case study

Ergonomic evaluation of visual demands becomes crucial for the operators/users when rapid decision making is needed under extreme time constraint like navigation task of jet aircraft. Research reported here comprises ergonomic evaluation of pilot's vision in a jet aircraft in virtual environment to demonstrate how vision analysis tools of digital human modeling software can be used effectively for such study. Three (03) dynamic digital pilot models, representative of smallest, average and largest Indian pilot population were generated from anthropometric database and interfaced with digital prototype of the cockpit in Jack software for analysis of vision within and outside the cockpit. Vision analysis tools like view cones, eye view windows, blind spot area, obscuration zone, reflection zone etc. were employed during evaluation of visual fields. Vision analysis tool was also used for studying kinematic changes of pilot's body joints during simulated gazing activity. From present study, it can be concluded that vision analysis tool of digital human modeling software was found very effective in evaluation of position and alignment of different displays and controls in the workstation based upon their priorities within the visual fields and anthropometry of the targeted users, long before the development of its physical prototype.     

Rao and Wu's re-scaling bootstrap modified to achieve extended coverages

Horvitz and Thompson's (HT) [1952. A generalization of sampling without replacement from a finite universe. J. Amer. Statist. Assoc. 47, 663–685] well-known unbiased estimator for a finite population total admits an unbiased estimator for its variance as given by [Yates and Grundy, 1953. Selection without replacement from within strata with probability proportional to size. J. Roy. Statist. Soc. B 15, 253–261], provided the parent sampling design involves a constant number of distinct units in every sample to be chosen. If the design, in addition, ensures uniform non-negativity of this variance estimator, Rao and Wu [1988. Resampling inference with complex survey data. J. Amer. Statist. Assoc. 83, 231–241] have given their re-scaling bootstrap technique to construct confidence interval and to estimate mean square error for non-linear functions of finite population totals of several real variables. Horvitz and Thompson's estimators (HTE) are used to estimate the finite population totals. Since they need to equate the bootstrap variance of the bootstrap estimator to the Yates and Grundy's estimator (YGE) for the variance of the HTE in case of a single variable, i.e., in the linear case the YG variance estimator is required to be positive for the sample usually drawn.     

Optimum designs for parameter estimation in a mixture experiment with two correlated responses

In this paper, we investigate a mixture problem with two responses, which are functions of the mixing proportions, and are correlated with known dispersion matrix. We obtain D- and A-optimal designs for estimating the parameters of the response functions, when none or some of the regression coefficients of the two functions are the same. It is shown that when no prior knowledge about the regression coefficients is available, the D-optimal design is independent of the dispersion matrix, while the A-optimal design depends on it, provided the response functions are of different degree. On the other hand, when some of the regression coefficients are known to be the same for both the functions, the D-optimal design depends on the dispersion matrix when the two response functions are not of the same degree.     

Causes of Neonatal Deaths among Tribal Women in Gujarat,India

Mortality among neonates has long been largely neglected by research in all developing nations of world including India. This study aims to identify the primary and secondary causes of neonatal deaths among the tribes of Gujarat by retrospectively analyzing 106 neonatal deaths that occurred during the year 2008 and 2009. The socio-economic, biological and traditional newborn care practices impacting newborn survival were also studied. Case studies including in-depth interviews of 33 women who had experienced neonatal deaths in period of 2008 and 2009 have also been conducted. The results show that the main causes of neonatal deaths in the study area were birth asphyxia, prematurity, aspiration, infection and congenital anomalies, irrespective of place of delivery. Absence of trained and skilled personnel for newborn resuscitation was the main cause of perinatal birth asphyxia related deaths. Around 36% mothers had a history of infant deaths. Low birth weight is one of the important causes of neonatal deaths among mothers who had a history of child loss. Cyclicality of neonatal deaths continued among clustered families with social factors initiating the cycle. Qualified trained birth attendants practicing essential newborn care are necessary during home deliveries.