The Positive Effects of Easy Goals on Decision Quality and Risk Propensity in an MCPLP Task

In this study the potential performance benefits of easy goals were examined within the multiple cue probability learning paradigm (MCPLP). Specifically, the effects of varying levels of goal difficulty on performance and risk propensity (used to define a form of commitment) were investigated. With few exceptions, previous studies demonstrated support for difficult goals. In this study, contrary to the majority of past evidence, as goals became easier decision quality significantly improved. Moreover, risk propensity increased with easier goals and, as suggested by a post-hoc analysis, had more direct impact on decision makers’ behaviors than goal levels. Goal-related behavior in complex MCPLP tasks appears to significantly differ from the majority of goal evidence in other types of research due to the tendency for subjects to view complex task properties in the same context as goal levels.     

A Rejoinder to Forman on AHP,with Emphasis on the Requirements of Composite Ratio Scales*

In an earlier paper [11], the problems of rank reversals and invalid composite priorities in AHP were addressed by modifications to the AHP procedure. That solution was subsequently criticized [5]. In this paper, we rebut these criticisms, and we show how rank reversals in AHP can arise merely from the process of normalizing local priorities.     

《天方性理》在伊斯兰教传统中的地位

一刘智的《天方性理》是18世纪和19世纪期间中国穆斯林最为广泛阅读的书之一,但该书后来逐渐为某些穆斯林学者所批评。批评此书的穆斯林学者认为,它从真正的伊斯兰教那里走岔了道。即便在今天,那些读此书的穆斯林或非穆斯林们都为这样的事实所触动,即它与通常描述的伊斯兰教义不完全相像。他们多半会问:这本书如何谈论伊斯兰教的呢?哪些地方被认为是穆斯林的内容呢?比如从《古兰经》、先知穆罕默德和大权威作家那里引用的内容在哪里?礼仪的教导、教规和制度、穆斯林信仰的认主学阐述又在哪里呢?为什么会有如此多的新儒家专用术语?从笔者这方…     

Social Ills in Rich Countries: New Evidence on Levels,Causes, and Mediators

Social Indicators Research - The income inequality hypothesis claims that in rich societies inequality causes a range of health and social problems (henceforth: social ills), e.g. because economic...     

Income Inequality across the Rural-Urban Continuum in the United States, 1970–2016*

The growth in macro-level income inequality in the United States is well established, but less is known about patterns of inequality at subnational scales and how they vary between and within rural and urban localities. Using data from the Decennial Census and American Community Survey, we produce estimates of within-county income inequality from 1970 to 2016 and analyze differences in inequality levels, the persistence of high (low) inequality, and populations' exposure to high (low) inequality across the rural-urban continuum. We find that income inequality has historically been higher in non-metropolitan than metropolitan counties, but inequality levels converged by 2016 due to growing inequality in metropolitan counties. Additionally, levels of inequality were generally persistent within counties over time, except that counties characterized by low inequality in 1970 were unlikely to remain as such in 2016. Third, non-trivial shares of the metropolitan population resided in low-inequality contexts in 1970, but virtually none of the U.S. population resided in such places by 2016. Residence in high-inequality counties is normative in rural and urban America. This statistical analysis provides an updated portrait of income inequality across the rural-urban continuum, and should spur additional research on stratification in rural America during an era of growing inequality.     

What’s in a yardscape? A case study of emergent ecosystem services and disservices within resident yardscape discourses in Minnesota

Urban Ecosystems - Residential yardscapes are at the forefront of human interaction with nature for those living in urban areas across Europe and North America. In recent years a significant amount...     

Ageing Population: Identifying the Determinants of Ageing in the Least Developed Countries

Population Research and Policy Review - The issue of population ageing is no longer exclusively centred on developed countries. Empirical studies have proven that the rise in the proportion of the...     

An elastic-net penalized expectile regression with applications

To perform variable selection in expectile regression, we introduce the elastic-net penalty into expectile regression and propose an elastic-net penalized expectile regression (ER-EN) model. We then adopt the semismooth Newton coordinate descent (SNCD) algorithm to solve the proposed ER-EN model in high-dimensional settings. The advantages of ER-EN model are illustrated via extensive Monte Carlo simulations. The numerical results show that the ER-EN model outperforms the elastic-net penalized least squares regression (LSR-EN), the elastic-net penalized Huber regression (HR-EN), the elastic-net penalized quantile regression (QR-EN) and conventional expectile regression (ER) in terms of variable selection and predictive ability, especially for asymmetric distributions. We also apply the ER-EN model to two real-world applications: relative location of CT slices on the axial axis and metabolism of tacrolimus (Tac) drug. Empirical results also demonstrate the superiority of the ER-EN model.