An omnibus two-sample test for ranked-set sampling data

We develop an omnibus two-sample test for ranked-set sampling (RSS) data. The test statistic is the conditional probability of seeing the observed sequence of ranks in the combined sample, given the observed sequences within the separate samples. We compare the test to existing tests under perfect rankings, finding that it can outperform existing tests in terms of power, particularly when the set size is large. The test does not maintain its level under imperfect rankings. However, one can create a permutation version of the test that is comparable in power to the basic test under perfect rankings and also maintains its level under imperfect rankings. Both tests extend naturally to judgment post-stratification, unbalanced RSS, and even RSS with multiple set sizes. Interestingly, the tests have no simple random sampling analog.     

Impact of metabolic status on the association of serum vitamin D with hypogonadism and lower urinary tract symptoms/benign prostatic hyperplasia

Objective: The objective of this study is to investigate the impact of metabolic status on associations of serum vitamin D with hypogonadism and lower urinary tract symptoms (LUTS)/benign prostatic hyperplasia (BPH).

Patients and methods: A total of 612 men underwent physical examination, biochemical/hormonal blood testing, and transrectal prostate ultrasound. Moreover, the subjects filled out standard questionnaires for identification and grading of LUTS and hypogonadism symptoms. Parameters were statistically compared with independent t-tests and correlation analyses.

Results: Vitamin D levels positively correlated with total testosterone (TT) but not with prostate volume or International Prostate Symptom Score (IPSS). Patients with metabolic syndrome had significantly lower vitamin D levels, which were not correlated with TT, prostate volume, or IPSS. However, vitamin D was positively correlated with TT, and negatively correlated with prostate volume and quality-of-life IPSS in subjects without metabolic syndrome.

Conclusion: The clinical usefulness of vitamin D for treatment of hypogonadism or LUTS/BPH varies according to metabolic status.     

From smiling to smirking? 3D printing,upgrading and the restructuring of global value chains

3D printing (3DP) has been heralded as a revolutionary technology that can alter the way production is organized across time and space – with important redistributive effects on geography and size of production activities. In this article, we examine the impacts that a widespread adoption of 3DP could have on restructuring, upgrading and distributing value added along manufacturing global value chains (GVC) – with brief examples from the aerospace and automotive industries. We highlight two possible scenarios for GVCs – a complementarity scenario of 3DP and traditional manufacturing overlapping, which would reproduce power relations in GVCs and the current distribution of value added in a ‘smiling curve’; and a substitution scenario of 3DP partly or fully superseding traditional manufacturing, which would have more transformational effects in terms of ‘rebundling’ activities, regionalizing or localizing GVCs, and flattening the smiling curve into a ‘smirk’.     

政府补贴对企业真实创新绩效的影响——基于中国A股上市公司数据的实证分析

在分析政府补贴政策的特征及其影响企业真实创新绩效的理论机制的基础上,运用A股上市公司数据,检验了政府补贴对企业真实创新绩效的直接和传导效应。研究发现：政府补贴对企业真实创新绩效具有激励效应,且国有企业较非国有企业的创新效应更强;研发资本要素市场扭曲能够强化政府补贴激励企业真实创新绩效的调节作用,并与产权性质联合调节政府创新补贴效果;创新投入与融资约束在政府补贴对企业真实创新绩效的影响中起部分中介效应;政府补贴对企业创新持续性具有负向抑制效应,政府补贴效果受到研发资本要素市场扭曲和产权性质明显的负向调节作用,且创新投入与融资约束在政府补贴对企业持续性创新的影响中起部分中介效应。     

莫言小说《丰乳肥臀》中的3D细节描写

3D细节描写是一种立体的3D视角,能将平面的画面直观地显现成3维的立体画面。《丰乳肥臀》中有大量的细节描写,有一部分是明显的3D描写,让读者融入情景、直观感受。尽管莫言不是有意识进行3D描写,但有意识地立体地细节描写写出了3D效果。     

Gender differences in risk behavior and the link to household effects and individual wealth

This study examined the differences in risk behavior between men and women using a household survey that captured the risk preferences of two members in a household and recorded wealth at the individual level instead of the usual approach of representing wealth at the household level. After controlling for commonly used explanatory variables, such as gender, education, age, and wealth, household fixed effects explain about 15% of the variation in risk behavior. This highlights the magnitude of household effects in shaping one’s risk behavior. In general, females in the study area are more risk averse than males based on a risk game with real payout. The gender differences disappear when focusing on only the top land owners. However, even in those cases, females consider themselves more risk averse, supporting results from previous studies that link culture and societal norms to the gender differences in risk behavior.     

Influencing behaviour: The mindspace way

The ability to influence behaviour is central to many of the key policy challenges in areas such as health, finance and climate change. The usual route to behaviour change in economics and psychology has been to attempt to ‘change minds’ by influencing the way people think through information and incentives. There is, however, increasing evidence to suggest that ‘changing contexts’ by influencing the environments within which people act (in largely automatic ways) can have important effects on behaviour. We present a mnemonic, MINDSPACE, which gathers up the nine most robust effects that influence our behaviour in mostly automatic (rather than deliberate) ways. This framework is being used by policymakers as an accessible summary of the academic literature. To motivate further research and academic scrutiny, we provide some evidence of the effects in action and highlight some of the significant gaps in our knowledge.     

Sex, self-interest and health care priorities

In this questionnaire study, individuals were asked to prioritise publicly provided preventive health care services, one of which would be unavailable to them by virtue of their sex. The aim was to establish whether men and women would exhibit different degrees of self-interest when making a constrained choice. Around 1800 subjects from east-central England prioritised three different types of cancer screening. Most also provided written explanations for their rankings and these were classified into explanatory themes. Logistic regressions using socio-demographic and attitude data predicted the type of screening chosen as first priority. The analysis revealed that many men and women did indeed assign similar priorities to the different types of screening and, even when the priorities differed, these were often justified by similar arguments relating to technical aspects of the interventions and to self-interest. However, women were far more likely than men to prioritise a type of screening from which they themselves would benefit directly and the variations in preferences and explanations between the sexes occurred primarily because of differences in other-regarding attitudes. The bias towards screening of females was driven by women's greater worries about the disease in question and by men's “benevolent sexism” with respect to women's wellbeing.     

A multicriteria sorting approach based on data envelopment analysis for R&D project selection problem

In this paper, multiple criteria sorting methods based on data envelopment analysis (DEA) are developed to evaluate research and development (R&D) projects. The weight intervals of the criteria are obtained from Interval Analytic Hierarchy Process and employed as the assurance region constraints of models. Based on data envelopment analysis, two threshold estimation models, and five assignment models are developed for sorting. In addition to sorting, these models also provide ranking of the projects. The developed approach and the well-known sorting method UTADIS are applied to a real case study to analyze the R&D projects proposed to a grant program executed by a government funding agency in 2009. A five level R&D project selection criteria hierarchy and an assisting point allocation guide are defined to measure and quantify the performance of the projects. In the case study, the developed methods are observed to be more stable than UTADIS.     

Optimum covariate designs in partially balanced incomplete block (PBIB) design set-ups

The use of covariates in block designs is necessary when the covariates cannot be controlled like the blocking factor in the experiment. In this paper, we consider the situation where there is some flexibility for selection in the values of the covariates. The choice of values of the covariates for a given block design attaining minimum variance for estimation of each of the parameters has attracted attention in recent times. Optimum covariate designs in simple set-ups such as completely randomised design (CRD), randomised block design (RBD) and some series of balanced incomplete block design (BIBD) have already been considered. In this paper, optimum covariate designs have been considered for the more complex set-ups of different partially balanced incomplete block (PBIB) designs, which are popular among practitioners. The optimum covariate designs depend much on the methods of construction of the basic PBIB designs. Different combinatorial arrangements and tools such as orthogonal arrays, Hadamard matrices and different kinds of products of matrices viz. Khatri–Rao product, Kronecker product have been conveniently used to construct optimum covariate designs with as many covariates as possible.