Empirical Bayes estimation in finite population sampling under functional measurement error models

The paper considers simultaneous estimation of finite population means for several strata. A model-based approach is taken, where the covariates in the super-population model are subject to measurement errors. Empirical Bayes (EB) estimators of the strata means are developed and an asymptotic expression for the MSE of the EB estimators is provided. It is shown that the proposed EB estimators are “first order optimal” in the sense of Robbins [1956. An empirical Bayes approach to statistics. In: Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, University of California Press, Berkeley, pp. 157–164], while the regular EB estimators which ignore the measurement error are not.     

Optimal Designs for Binary Logistic Regression with a Qualitative Classifier with Independent Levels

Dose response studies arise in many medical applications. Often, such studies are considered within the framework of binary-response experiments such as success-failure. In such cases, popular choices for modeling the probability of response are logistic or probit models. Design optimality has been well studied for the logistic model with a continuous covariate. A natural extension of the logistic model is to consider the presence of a qualitative classifier. In this work, we explore D-, A-, and E-optimal designs in a two-parameter, binary logistic regression model after introducing a binary, qualitative classifier with independent levels.     

Measuring Multidimensional Poverty According to National Definitions: Operationalising Target 1.2 of the Sustainable Development Goals

Social Indicators Research - The first Sustainable Development Goal (SDG) tasks countries with eradicating poverty in all its dimensions according to national definitions. This presents...     

Applying the Consensual Method of Estimating Poverty in a Low Income African Setting

Social Indicators Research - We present the first study of multidimensional poverty in Benin using the consensual or socially perceived necessities approach. There is a remarkable level consensus...     

Health Financing in Singapore: A Case for Systemic Reforms

This paper assesses Singapore's healthcare financing arrangements in terms of their efficiency, fairness, and adequacy. Singapore represents an interesting case study because it is perhaps the only high‐income, rapidly ageing country to rely on mandatory savings to finance healthcare, thus eschewing extensive risk‐pooling arrangements, generally regarded as efficient and equitable. The paper argues that parametric reforms, i.e. relatively minor changes in the parameters of current schemes which preserve the existing philosophy and system design, will not be sufficient to meet healthcare financing objectives. Systemic reforms, which will bring Singapore into the mainstream of health financing arrangements found in the OECD countries, are urgently needed. Their design and timing should be based on good quality, timely and relevant data, and an environment conducive to vigorous debate.     

Kinship care in the UK: using census data to estimate the extent of formal and informal care by relatives

Until recently, little was known about kinship care in the UK. Research has begun to illuminate the circumstances which lead to children being cared for by relatives, and the stresses and strains experienced by carers. However, most UK research has only considered ‘looked‐after’ children placed with formal approved kinship foster carers, although this group forms the smallest proportion of children in kinship arrangements. In this paper, we use microdata from the 2001 UK Population Census to examine the characteristics of kinship carers and children, and demonstrate that most children in kinship care are growing up in informal unregulated arrangements. Implications for policy and practice are discussed.     

Analysis of dose-response in flexible dose titration clinical studies

Assessing dose-response from flexible-dose clinical trials (e.g., titration or dose escalation studies) is challenging and often problematic due to the selection bias caused by 'titration-to-response'. We investigate the performance of a dynamic linear mixed-effects (DLME) model and marginal structural model (MSM) in evaluating dose-response from flexible-dose titration clinical trials via simulations. The simulation results demonstrated that DLME models with previous exposure as a time-varying covariate may provide an unbiased and efficient estimator to recover exposure-response relationship from flexible-dose clinical trials. Although the MSM models with independent and exchangeable working correlations appeared to be able to recover the right direction of the dose-response relationship, it tended to over-correct selection bias and overestimated the underlying true dose-response. The MSM estimators were also associated with large variability in the parameter estimates. Therefore, DLME may be an appropriate modeling option in identifying dose-response when data from fixed-dose studies are absent or a fixed-dose design is unethical to be implemented.     

Singapore's policy responses to ageing, inequality and poverty: An assessment

Abstract   Singapore represents an instructive case study in responding to rapid ageing, growing inequalities, and significant relative poverty. Unlike other high-income Asian countries, it has relied on single-tier mandatory savings to finance retirement, housing, and to a lesser extent, healthcare. To address the low fertility rates, it has permitted the share of the non-citizen population to triple between 1990 and 2005 to nearly 30 per cent. This is subtly altering Singapore's socio-political dynamics, while assisting in sustaining growth and competitiveness. The paper argues that Singapore has the fiscal, institutional, and organizational capacities for a modern multi-tier social security system. Singapore is, however, determined to continue with current inadequate and inequitable arrangements, requiring individuals and their families to bear disproportionate risks in financing retirement, healthcare, and short-term income support. This reflects conscious policy choices arising from a Darwinist vision of society, and the need for socio-political control.     

Some variations on constrained minimum enclosing circle problem

Given a set P of n points and a straight line L, we study three important variations of minimum enclosing circle problem as follows:

1. Computing k identical circles of minimum radius with centers on L, whose union covers all the points in P.
2. Computing the minimum radius circle centered on L that can enclose at least k points of P.
3. If each point in P is associated with one of the k given colors, then compute a minimum radius circle with center on L such that at least one point of each color lies inside it.

We propose three algorithms for Problem (i). The first one runs in O(nklogn) time and O(n) space. The second one is efficient where k?n; it runs in O(nlogn+nk+k ²log³ n) time and O(nlogn) space. The third one is based on parametric search and it runs in O(nlogn+klog⁴ n) time. For Problem (ii), the time and space complexities of the proposed algorithm are O(nk) and O(n) respectively. For Problem (iii), our proposed algorithm runs in O(nlogn) time and O(n) space.