Analysis of error-prone survival data under additive hazards models: measurement error effects and adjustments

Covariate measurement error occurs commonly in survival analysis. Under the proportional hazards model, measurement error effects have been well studied, and various inference methods have been developed to correct for error effects under such a model. In contrast, error-contaminated survival data under the additive hazards model have received relatively less attention. In this paper, we investigate this problem by exploring measurement error effects on parameter estimation and the change of the hazard function. New insights of measurement error effects are revealed, as opposed to well-documented results for the Cox proportional hazards model. We propose a class of bias correction estimators that embraces certain existing estimators as special cases. In addition, we exploit the regression calibration method to reduce measurement error effects. Theoretical results for the developed methods are established, and numerical assessments are conducted to illustrate the finite sample performance of our methods.     

Gender Differences in Happiness and Life Satisfaction Among Adolescents in Hong Kong: Relationships and Self-Concept

This study uses survey data from adolescents (N = 1,428) in Hong Kong to test the association of gender with happiness and life satisfaction through relationship style and self-concept. While self-esteem and purpose in life are associated with higher happiness and life satisfaction, having more close friends is related to higher happiness, but not necessarily life satisfaction. On the other hand, boys with higher academic achievement are happier, but not more satisfied; the opposite holds true for girls. Our results provide a much-needed investigation of the differential effect of gender on the subjective well-being of adolescents. Contributing to the theoretical debate about the concepts of subjective well-being, we argue that happiness and life satisfaction are empirically and conceptually distinct. Life satisfaction might be characterized by more profound enjoyment and achievement in life than happiness.     

COVID-19 vaccine rollout—scale and speed carry different implications for corruption

The sanctioning of different coronavirus vaccines (with some approved by regulators for public delivery, and others in the pipeline) has met with relief by many sections of the public and the government. However, partly due to the damages associated with the pandemic and the ensuing euphoria over vaccines’ arrival, some of the challenges are mostly being ignored or are not recognized. This paper identifies some pitfalls and drawbacks in vaccine delivery. We argue that the somewhat unique tension between the speed of vaccine delivery and its scale can create opportunities for corrupt behavior that are often at odds with effective means to check abuse. While data on instances of abuse will emerge over time, it is useful to point out different avenues of abuse so that some preventive government actions can be undertaken. Specifically, we argue that the potential for out of turn delivery of vaccines and the stockpiling by unauthorized agents creates incentives for corruption, with the public or bureaucrats initiating corrupt transactions. An understanding of the potential avenues for corruption should guide the formulation of appropriate corruption-control policies and similar challenges that will be faced by policy makers in addressing future pandemics.     

Economic distress and health: A fixed effects analysis of low‐income persons in Singapore

Using fixed effects regressions, this study examined the transactional effects of different types of economic status on the physical and mental health of low‐income persons in Singapore. Among the economic variables considered, unemployment and arrears had the most significant effects. This signals the physical and psychological distress of being out of work and possessing arrears while income is low. The insignificant effects of poor health on household earnings suggest possible earnings supplementation by other household members. The findings imply the fruitfulness of dually improving employment prospects and health, work activation that takes into consideration mental health effects, increasing affordability of health services in liberal welfare systems, improving mental bandwidth through reducing arrears accounts, and short lag time from application to receipt of assistance. These implications point to a larger question on health and welfare systems in an increasingly uncertain economic environment for households in poverty. Key Practitioner Message: ? Employment and health are inter‐related: employment assistance incorporating physical and mental health interventions and vice versa can be more effective than either alone; ? Compared with decreasing arrears amounts, reducing the number of arrears can more effectively relieve mental distress; ? Effects between economic distress and health materialise quickly; minimising the lag time between application and receipt of assistance will provide great relief.     

Diagnostics on nonlinear model with scale mixtures of skew-normal and first-order autoregressive errors

In this work, we develop some diagnostics for nonlinear regression model with scale mixtures of skew-normal (SMSN) and first-order autoregressive errors. The SMSN distribution class covers symmetric as well as asymmetric and heavy-tailed distributions, which offers a more flexible framework for modelling. Maximum-likelihood (ML) estimates are computed via an expectation–maximization-type algorithm. Local influence diagnostics and score test for the correlation are also derived. The performances of the ML estimates and the test statistic are investigated through Monte Carlo simulations. Finally, a real data set is used to illustrate our diagnostic methods.     

A multi-faced buildup algorithm for three-dimensional packing problems

This paper provides a new approach to solving the three-dimensional packing problem. The heuristic developed uses a multi-faced buildup technique in the packing procedure for which there is no requirement for packed boxes to form flat layers. The basic algorithm is then augmented by a Look-ahead strategy. Experimental results indicate an average packing utilization of 87.8% which improve current benchmarks significantly. The new approaches given here add to heuristics currently available.     

Online algorithms for 1-space bounded multi dimensional bin packing and hypercube packing

In this paper, we study 1-space bounded multi-dimensional bin packing and hypercube packing. A sequence of items arrive over time, each item is a d-dimensional hyperbox (in bin packing) or hypercube (in hypercube packing), and the length of each side is no more than 1. These items must be packed without overlapping into d-dimensional hypercubes with unit length on each side. In d-dimensional space, any two dimensions i and j define a space P _ij . When an item arrives, we must pack it into an active bin immediately without any knowledge of the future items, and 90^°-rotation on any plane P _ij is allowed. The objective is to minimize the total number of bins used for packing all these items in the sequence. In the 1-space bounded variant, there is only one active bin for packing the current item. If the active bin does not have enough space to pack the item, it must be closed and a new active bin is opened. For d-dimensional bin packing, an online algorithm with competitive ratio 4 ^d is given. Moreover, we consider d-dimensional hypercube packing, and give a 2 ^d+1-competitive algorithm. These two results are the first study on 1-space bounded multi dimensional bin packing and hypercube packing.     

Online algorithms for maximizing weighted throughput of unit jobs with temperature constraints

We consider a temperature-aware online deadline scheduling model. The objective is to schedule a number of unit jobs, with release dates, deadlines, weights and heat contributions, to maximize the weighted throughput subject to a temperature threshold. We first give an optimally competitive randomized algorithm. Then we give a constant competitive randomized algorithm that allows a tradeoff between the maximum heat contribution of jobs and the competitiveness. Finally we consider the multiple processor case and give several tight upper and lower bounds.     

Early Sales of Seasonal Products with Weather‐Conditional Rebates

Some retailers of seasonal products adopt weather‐conditional rebate programs to induce early sales and increase profits. In such promotions, customers who buy the product in an advance preselling period are offered rebates if a pre‐specified weather condition is realized during the later normal selling season. We investigate the potential benefits of these programs for retailers. We show that the weather‐conditional rebate program can increase sales by price discriminating among a customer's post‐purchase states. Taking advantage of the early sales, it can also reduce the inventory holding cost and ordering cost, and hence can increase the retailer's expected profits. In addition, we numerically investigate the sensitivity of the rebate program's effectiveness to the model parameters and illustrate its advantages over an advance‐discount policy.     

构建和谐社会与扩大中等收入者群体比重

扩大中等收入者群体比重,是缩小城乡差距、地区差距和社会阶层差距的需要,也是构建和谐社会的需要.要实现构建社会主义和谐社会的发展战略,就必须坚持在发展中解决问题,要在经济总量不断做大、整体收入不断提高的基础上扩大中等收入者比重,扩大中等收入者群体的数量和质量,最终朝构建和谐社会的目标迈进.