Observed Emotions as Predictors of Quality of Kindergartners’ Social Relationships

This study evaluated whether positive and anger emotional frequency (the proportion of instances an emotion was observed) and intensity (the strength of an emotion when it was observed) uniquely predicted social relationships among kindergarteners (N = 301). Emotions were observed as naturally occurring at school in the fall term and multiple reporters (peers and teachers) provided information on quality of relationships with children in the spring term. In structural equation models, positive emotion frequency, but not positive emotion intensity, was positively related to peer acceptance and negatively related to peer rejection. In contrast, the frequency of anger provided unique positive prediction of teacher–student conflict and negative prediction of peer acceptance. Furthermore, anger intensity negatively predicted teacher–student closeness and positively predicted teacher–student conflict. Implications for promoting social relationships in school are discussed.     

The duality of poverty: a replication of Mani et al. (2013) in Colombia

Theory and Decision - Scarcity acts as a mental burden that disrupts how people process information and make decisions (Mullainathan and Shafir in Scarcity: Why having too little means so much....     

Beyond Self‐Reports: Changes in Biomarkers as Predictors of Mortality

The proliferation of biosocial surveys has increased the importance of weighing the costs and benefits of adding biomarker collection to population‐based surveys. A crucial question is whether biomarkers offer incremental value beyond self‐reported measures, which are easier to collect and impose less respondent burden. We use longitudinal data from a nationally representative sample of older Taiwanese (aged 54+ in 2000, examined in 2000 and 2006 with mortality follow‐up through 2011) to address that question with respect to predicting all‐cause mortality. A summary measure of biomarkers improves mortality prediction (as measured by the area under the receiver operating characteristic curve) compared with self‐reports alone, but individual biomarkers perform better than the summary score. We find that incorporating change in biomarkers over a six‐year period yields a small improvement in mortality prediction compared with one‐time measurement. But, is the incremental value worth the costs?     

Perceptions of Migration and Diversity by Local Public Administrators

This article contributes to the recent debate on the perception of migration and diversity; it empirically examines whether public decision-makers and public administrators perceive migration and diversity as related or if they distinguish between them. It also seeks to identify the most important characteristics of respondents with positive attitudes to migration and diversity. The sample of the respondents covers Turkey, Greece, Hungary and Slovakia; those located on the “Balkan migration route” into Europe. Due to different experiences, respondents from countries with large-scale migration perceive migration and diversity differently from those in countries directly threatened by migration or countries without any direct impact of migration. Gender appears to be a statistically significant predictor in the need for high managerial skills to manage migration and diversity. Some size categories of municipalities where a respondent works appear to be statistically significant when ranking the local impacts and local economic benefits of migration.     

Robust inference in an heteroscedastic measurement error model

In this paper we deal with robust inference in heteroscedastic measurement error models. Rather than the normal distribution, we postulate a Student t distribution for the observed variables. Maximum likelihood estimates are computed numerically. Consistent estimation of the asymptotic covariance matrices of the maximum likelihood and generalized least squares estimators is also discussed. Three test statistics are proposed for testing hypotheses of interest with the asymptotic chi-square distribution which guarantees correct asymptotic significance levels. Results of simulations and an application to a real data set are also reported.     

A nonparametric symmetry test for absolutely continuous bivariate copulas

Based on the works by Klement and Mesiar (Comment Math Univ Carolinae 47:141–148, 2006) and Nelsen (Stat Pap 48:329–336, 2007) on maximal asymmetry of copulas, we define and study the concept of tri-symmetry and we propose a simple statistic to test symmetry of a bivariate copula, given a random sample of an absolutely continuous bivariate random vector. We also make a power comparison against some other well known nonparametric symmetry tests.     

Small area estimation under random regression coefficient models

Statistical agencies are interested to report precise estimates of linear parameters from small areas. This goal can be achieved by using model-based inference. In this sense, random regression coefficient models provide a flexible way of modelling the relationship between the target and the auxiliary variables. Because of this, empirical best linear unbiased predictor (EBLUP) estimates based on these models are introduced. A closed-formula procedure to estimate the mean-squared error of the EBLUP estimators is also given and empirically studied. Results of several simulation studies are reported as well as an application to the estimation of household normalized net annual incomes in the Spanish Living Conditions Survey.