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.     

Penalized least squares smoothing of two-dimensional mortality tables with imposed smoothness

This paper presents a method to estimate mortality trends of two-dimensional mortality tables. Comparability of mortality trends for two or more of such tables is enhanced by applying penalized least squares and imposing a desired percentage of smoothness to be attained by the trends. The smoothing procedure is basically determined by the smoothing parameters that are related to the percentage of smoothness. To quantify smoothness, we employ an index defined first for the one-dimensional case and then generalized to the two-dimensional one. The proposed method is applied to data from member countries of the OECD. We establish as goal the smoothed mortality surface for one of those countries and compare it with some other mortality surfaces smoothed with the same percentage of two-dimensional smoothness. Our aim is to be able to see whether convergence exists in the mortality trends of the countries under study, in both year and age dimensions.     

Innovational Outliers in INAR(1) Models

We consider integer-valued autoregressive models of order one contaminated with innovational outliers. Assuming that the time points of the outliers are known but their sizes are unknown, we prove that Conditional Least Squares (CLS) estimators of the offspring and innovation means are strongly consistent. In contrast, CLS estimators of the outliers' sizes are not strongly consistent. We also prove that the joint CLS estimator of the offspring and innovation means is asymptotically normal. Conditionally on the values of the process at time points preceding the outliers' occurrences, the joint CLS estimator of the sizes of the outliers is asymptotically normal.     

The beta-Weibull geometric distribution

We propose a new distribution, the so-called beta-Weibull geometric distribution, whose failure rate function can be decreasing, increasing or an upside-down bathtub. This distribution contains special sub-models the exponential geometric [K. Adamidis and S. Loukas, A lifetime distribution with decreasing failure rate, Statist. Probab. Lett. 39 (1998), pp. 35–42], beta exponential [S. Nadarajah and S. Kotz, The exponentiated type distributions, Acta Appl. Math. 92 (2006), pp. 97–111; The beta exponential distribution, Reliab. Eng. Syst. Saf. 91 (2006), pp. 689–697], Weibull geometric [W. Barreto-Souza, A.L. de Morais, and G.M. Cordeiro, The Weibull-geometric distribution, J. Stat. Comput. Simul. 81 (2011), pp. 645–657], generalized exponential geometric [R.B. Silva, W. Barreto-Souza, and G.M. Cordeiro, A new distribution with decreasing, increasing and upside-down bathtub failure rate, Comput. Statist. Data Anal. 54 (2010), pp. 935–944; G.O. Silva, E.M.M. Ortega, and G.M. Cordeiro, The beta modified Weibull distribution, Lifetime Data Anal. 16 (2010), pp. 409–430] and beta Weibull [S. Nadarajah, G.M. Cordeiro, and E.M.M. Ortega, General results for the Kumaraswamy-G distribution, J. Stat. Comput. Simul. (2011). DOI: 10.1080/00949655.2011.562504] distributions, among others. The density function can be expressed as a mixture of Weibull density functions. We derive expansions for the moments, generating function, mean deviations and Rénvy entropy. The parameters of the proposed model are estimated by maximum likelihood. The model fitting using envelops was conducted. The proposed distribution gives a good fit to the ozone level data in New York.     

Estimation of cost allocation coefficients at the farm level using an entropy approach

This paper aims to estimate the farm cost allocation coefficients from whole-farm input costs. An entropy approach was developed under a Tobit formulation and was applied to a sample of farms from the 2004 Farm Accountancy Data Network data base for Alentejo region, Southern Portugal. A Generalized Maximum Entropy model and Cross Generalized Entropy model were developed to the sample conditions and were tested. Model results were assessed in terms of their precision and estimation power and were compared with the observed data. The entropy approach showed to be a flexible and valid tool to estimate incomplete information, namely regarding farm costs.     

Testing the Personal Wellbeing Index on 12–16?Year-Old Adolescents in 3 Different Countries with 2 New Items

The 7-item adult version of the Personal Wellbeing scale (Cummins et al. Social Indic Res 64:159?C190, 2003) was administered to two samples of adolescents aged 12?C16 in Brazil (N?=?1,588) and Spain (N?=?2,900), and to a sample of adolescents aged 14?C16 in Chile (N?=?843). The results obtained were analyzed to determine its psychometric characteristics when used with adolescents in the three different countries and to check whether two additional items would improve its qualities. Results reveal that the new PWI-9 version worked well with the adolescents in the three countries, improving some of the qualities of the PWI-7. One of the added items, satisfaction with oneself, appears to be a major contributor to unique explained variance when regressed on the single-item of overall life satisfaction (OLS). The model we present using structural equations shows good fit statistics for the factor structure, with both 7 and 9 items. Separate in-country analyses demonstrate that cultural context has a strong influence on correlations and saturations between the studied variables and also on the explained variance. Probably related to this fact, the Model fit structure is good in Brazil (with a low PWI variance accounted for by its predictors) and Spain (medium), but rather modest in Chile, where data show a high proportion of the PWI variance accounted for by its predictors. However, a multi-group factor analysis among the three countries restricting saturations to 1 in each country in order to make data comparable across countries still show a good fit of the proposed model for both PWI-7 and PWI-9.     

A class of beta regression models with multiplicative log-normal measurement errors

In this article, we propose a beta regression model with multiplicative log-normal measurement errors. Three estimation methods are presented, namely, naive, calibration regression, and pseudo likelihood. The nuisance parameters are estimated from a system of estimation equations using replicated data and these estimates are used to propose a pseudo likelihood function. A simulation study was performed to assess some properties of the proposed methods. Results from an example with a real dataset, including diagnostic tools, are also reported.     

Survival Weibull regression model for mismeasured outcomes

In some survival studies, the exact time of the event of interest is unknown, but the event is known to have occurred during a particular period of time (interval-censored data). If the diagnostic tool used to detect the event of interest is not perfectly sensitive and specific, outcomes may be mismeasured; a healthy subject may be diagnosed as sick and a sick one may be diagnosed as healthy. In such cases, traditional survival analysis methods produce biased estimates for the time-to-failure distribution parameters (Paggiaro and Torelli 2004 Paggiaro, A., and N. Torelli. 2004. The effect of classification errors in survival data analysis. Statistical Methods and Applications 13:213–25.[Crossref] , [Google Scholar]). In this context, we developed a parametric model that incorporates sensitivity and specificity into a grouped survival data analysis (a case of interval-censored data in which all subjects are tested at the same predetermined time points). Inferential aspects and properties of the methodology, such as the likelihood function and identifiability, are discussed in this article. Assuming known and non differential misclassification, Monte Carlo simulations showed that the proposed model performed well in the case of mismeasured outcomes; the estimates of the relative bias of the model were lower than those provided by the naive method that assumes perfect sensitivity and specificity. The proposed methodology is illustrated by a study related to mango tree lifetimes.     

论原始儒家的"圣人" 理想

“圣人”是儒家思想中一个重要范畴。儒家的“圣人”观念与巫文化时期的“巫”存在着渊源关系 :圣人由巫演化而来 ;先秦儒家诸子的政治实践 ,直接促成了这一转变演化 ,也就是说 ,儒家诸子的政治实践过程也就是他们对“圣人”政治理想的构建过程 ;巫之所以能演化为“圣”和“圣人” ,有深刻的理论根源、社会历史原因和独特的社会经济根源     

Residuals for log-Burr XII regression models in survival analysis

In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to the modified martingale-type residual in log-Burr XII regression models with censored data.