Spatial Sampling Design for a Demographic and Health Survey

The recent advances in global position systems (GPS), geographic information systems (GIS), and remote sensing (RS) can be exploited for spatial sampling design for demographic and health surveys. These technologies are particularly useful when a sampling frame is unavailable and/or location (of household) is important for data collection (e.g., location of residence might greatly impact exposure to ambient air pollution among members of a population). Building on these technologies, this article presents a methodology of spatial sampling adopted for the respiratory health and demographic survey conducted in Delhi and its environs from January through April 2004. The overall goal of the survey was to select households that adequately represented exposure to ambient air pollution. The proposed methodology involved constructing a sampling frame of residential areas and the simulation of weighted random points within residential areas. The simulated locations were navigated with the aid of GPS to identify households at these locations and to acquire residents’ consent to participate in the survey; a total of 1,576 households at the 2,000 simulated locations were found suitable and participated in the survey. The average ambient air pollution at the sample sites was not significantly different from the average air pollution observed in the study area, which demonstrates the robustness of the proposed sampling method.     

Neo-natal mortality in South Asia: The special role of tetanus

Summary First-year mortality in rural Uttar Pradesh is characterized by a predominance (60 per cent) of deaths during the first month of life, of which 66 per cent are reported to be due to tetanus. This pattern is not typical of the historical experience of many developed countries and the current experience of some less developed countries where post-neo-natal mortality predominates. To examine this phenomenon, two causal models of neo-natal mortality (one for tetanus and one for all other diseases) are developed and tested using retrospective survey data from 2000 couples living in rural Uttar Pradesh. Neo-natal tetanus mortality is found to be primarily a function of opportunities for exposure to the disease (e.g. lack of antiseptic birth practices, ownership of large animals) rather than of socio-economic status or demographic variables. The importance of examining neo-natal mortality by cause, and the shortcomings inherent in making inferences from the historical experiences of Western nations are emphasized.     

Estimation of smooth regression functions in monotone response models

We consider the estimation of smooth regression functions in a class of conditionally parametric co-variate-response models. Independent and identically distributed observations are available from the distribution of (Z,X)$(Z,X)$, where Z is a real-valued co-variate with some unknown distribution, and the response X conditional on Z   is distributed according to the density p(·,ψ(Z))$p(·,\psi (Z))$, where p(·,θ)$p(·,\theta )$ is a one-parameter exponential family. The function ψ$\psi$ is a smooth monotone function. Under this formulation, the regression function E(X|Z)$E(X|Z)$ is monotone in the co-variate Z   (and can be expressed as a one–one function of ψ$\psi$); hence the term “monotone response model”. Using a penalized least squares approach that incorporates both monotonicity and smoothness, we develop a scheme for producing smooth monotone estimates of the regression function and also the function ψ$\psi$ across this entire class of models. Point-wise asymptotic normality of this estimator is established, with the rate of convergence depending on the smoothing parameter. This enables construction of Wald-type (point-wise) as well as pivotal confidence sets for ψ$\psi$ and also the regression function. The methodology is extended to the general heteroscedastic model, and its asymptotic properties are discussed.     

On generalized conditional cumulative residual inaccuracy measure

Abstract

Recently, the notion of cumulative residual Rényi’s entropy has been proposed in the literature as a measure of information that parallels Rényi’s entropy. Motivated by this, here we introduce a generalized measure of it, namely cumulative residual inaccuracy of order α. We study the proposed measure for conditionally specified models of two components having possibly different ages called generalized conditional cumulative residual inaccuracy measure. Several properties of generalized conditional cumulative residual inaccuracy measure including the effect of monotone transformation are investigated. Further, we provide some bounds on using the usual stochastic order and characterize some bivariate distributions using the concept of conditional proportional hazard rate model.     

Proportional odds model – a quantile approach

The paper discusses a quantile-based definition for the well-known proportional odds model. We present various reliability properties of the model using quantile functions. Different ageing properties are derived. A generalization for the class of distributions with bilinear hazard quantile function is established and the practical application of this model is illustrated with a real-life data set.     

Operationalising lean in healthcare: the impact of professionalism

Abstract

Lean is endorsed as policy in practice in the UK but the challenges and complexities affecting Lean in healthcare are still to be adequately assessed. Through a qualitative single case study of an NHS organisation implementing Lean, 43 interviews with multi-disciplinary team members involved in Lean were conducted. The progress of Lean is found to be inhibited as medical professionals have failed to engage or provide clinical leadership in supporting the trajectory of Lean. This resulted in limited outcomes, sustainability implications, and failed projects. Lean is challenged by complexity and this is evident in conflicts between professional identity, corresponding status and clinical/managerial relationships. Medical professionals as a group have received a limited focus in papers assessing the progress of Lean in Healthcare from an operational perspective. Going forward, strategies for mitigating the negative impact of this can be developed to support operational managers in the healthcare domain.     

Optimal inventory cycle counting

The heart of inventory transactions management involves obtaining an accurate count of on-hand inventories employing different procedures. Among such procedures cycle counting is said to provide better inventory record accuracy for financial control and production planning. However, these procedures use rather arbitrary basis for classifying items and for setting the count frequency within each strata. This paper develops a simple optimization model of inventory cycle counting based on traditional stratified sampling theory. Such a model allows the inventory manager to make statistically supported statements regarding inventory record accuracy so as to meet financial control requirements with a minimum of cycle counting effort. A numerical example is included to illustrate the model.     

Addressing issues of face validity in the application of a clinical guideline

In 1995, a statewide project to improve the practice of electroconvulsive therapy (ECT) in the Medicare population was started in Louisiana. A retrospective baseline study found high concurrent utilization of lithium and benzodiazepines, medications considered detrimental to ECT by the second American Psychiatric Association Task Force on ECT. Resistance to a clinical guideline because of lack of face validity by clinicians was used as an opportunity to involve clinicians in using data to evaluate their clinical practices. Results of the first two quarters of the project demonstrated that the strategy was successful.