The study evaluated the stability over time of the Q-CHAT (i.e., Quantitative-CHecklist for Autism in Toddler), a screening tool for the early detection of Autism. The Q-CHAT is filled by parents when the child is from 18-36 months old, and whether a risk score is found, the clinician refers the child to a more in-depth diagnostic evaluation. Previous studies demonstrated the measure test-retest reliability on a small time interval (1-6 months). Therefore, the present study tested the stability of the scores considering a larger time interval of 18 months. No previous studies have tested its measurement invariance over time. Since the tool is filled by parents during a large time span (18-36 months of life), it is imperative to understand whether there is an invariance over time in their evaluations. The Italian version of the Q-CHAT was completed by 282 parents of children with no pre-existing signs of risk of Autism. The Q-CHAT was administered when children were 18 months (T1) and then 18 months later (T2). The intraclass correlation coefficients for the test-retest reliability ranged from sufficient to moderate. The measurement invariance across time revealed a tolerable configural and metric invariance. Contrary, the scalar invariance was not met meaning that the means of the constructs are not invariant over time. The findings give a further demonstration of the reliability of the Q-CHAT. They give evidence that changes in the scores would reflect real changes in the construct itself, and not in the way individuals interpret the measure items.

Nowadays, the labour market’s instability and flexibility has led to increased feelings of uncertainty, insecurity and precariousness in the workforce. With respect to psychological health, to date studies focused mainly on the consequences of the fear of losing the job as a whole (i.e. quantitative job insecurity), in comparison to the consequences of threat of losing valued job features (i.e. qualitative job insecurity). Understanding the psychological mechanisms that explain the process of stress experiences, deriving from qualitative job insecurity, may contribute to identify how to promote healthier workplaces. The present study aimed to examine the mediating role of precariousness of life in the relationship between qualitative job insecurity and mental distress, i.e. emotional exhaustion and psychological symptoms. Precariousness of life is a pervasive syndrome among temporary employees affecting their daily life. The Conservation Of Resources (COR) and dual labour market theories were used as theoretical framework to draw the research hypotheses. The sample was composed of 272 white and blue collar Italian temporary employees. The results of structural equation modelling revealed that qualitative job insecurity was positively and significantly related to emotional exhaustion and psychological symptoms. Furthermore, these relationships were mediated by precariousness of life: Goodness of fit indices of mediation model was satisfactory and indirect effects were significant, therefore supporting our hypotheses. This study provided additional evidence to the literature concerning job insecurity as it focused on temporary workers, examining the effect on mental health by qualitative job insecurity via precariousness of life. Practical implications were discussed.

The STATIS method is one of many strategies of analysis devoted to the unsupervised analysis of multiblock data. A new optimization criterion to define this method of analysis is introduced and an extension to the cluster analysis of several blocks of variables is discussed. This consists in a hierarchical cluster analysis and a partitioning algorithm akin to the K-means algorithm. Moreover, in order to improve the cluster analysis outcomes, an additional cluster called noise cluster which contains atypical blocks of variables is introduced. The general strategy of analysis is illustrated by means of two cases studies.

This paper aims to detect which are the drivers leading to victory for basketball matches in NBA, the American National Basketball Association. First games for regular seasons from 2004-2005 to 2017-2018 have been summarized in terms of box scores and Dean's four factors. Then box scores and four factors have been used as classication independent variables to identify victory drivers, focusing on Golden StateWarriors matches. Both CART and Random Forests machine learning techniques have been applied, and results are compared to assess the more suitable approach.

In the current socio-economic scenario, affected by constant changes inthe labor market, employability found greater echo. Universities frequently adopt strategies aimed at improving the employability and usefulness of theareas of competence, motivation and interests of young graduates and workers. In this study a preliminary research was conducted on a sample of 84 university students who attended a consulting service at the University of Salento, the Career Service Office. The average age of the sample was 26.74 years (DS = 4.95), 63% women, 71.4% unemployed. The tool used was a questionnaire-interview. The aim of this research was to assess the role of employability and its influence on personal variables and active work behaviours, as job searching activities. Analyses were conducted through PLS-PM technique, a non-parametrical SEM modeling, and demonstrated that employability affects job search and personal efficacy, while personal efficacy had a non signicant relation with job search behaviours.

In this work, we are interested in a hypothesis testing problem within the framework of a GPD model with interval censoring. For this purpose, we rst develop the calculation of the likelihood function using conditional probabilities to achieve the same expression proposed by Klein and Moeschberger. Next, we show that the properties of the maximum pseudo-likelihood estimates of the model parameters, and essentially the asymptotic normality, are preserved. Finally, we built a hypothesis testing to compare two types of breast cancer treatment as part of the model mentioned above.

Statistical knowledge and expertise are gaining importance during this era of information and knowledge economy (KE). In addition to the fundamental role they play in R&D, statistical methods and techniques are widely utilized to assess knowledge output and performance of knowledge economies. This paper provides an overview of the use of statistics in the workplace in the United Arab Emirates (UAE), and the role statistics and statisticians play in the country's endeavors to transform to a KE. The paper further elucidates the gap between statistics education and the labor market needs. Information are garnered from a sample of 104 statisticians and practitioners with related backgrounds on several issues covering the level of statistical practice in the country, training and professional development and the role statisticians play in supporting research and decision making. Evidence reveals a growing recognition of the role of statistics in the country. Several limitations, however, were noted including increased shortages in supply of statisticians and a lack of indepth professional training in traditional and emerging statistics topics together with a lack of quality research output.

Lasso regression methods are widely used for a number of scientic applications.Many practitioners of statistics were not aware that a small changein the data would results in unstable Lasso solution path. For instance, inthe presence of outlying observations, Lasso perhaps leads the increase inthe percentage of the false selection rate of predictors. On the other hand,the discussions on determining an optimal shrinkage parameter of Lasso isstill ongoing. Therefore, this paper proposed a robust algorithm to tacklethe instability of Lasso in the presence of outliers. A new weight function isproposed to overcome the problem of outlying observations. The weightedobservations are subsamples for a certain number of subsamples to controlthe false Lasso selection. The simulation study has been carried out and usesreal data to assess the performance of our proposed algorithm. Consequently,the proposed method shows more eciency than LAD-Lasso and weightedLAD-Lasso and more reliable results.

Customer Satisfaction management has been long studied as a cross-sectional phenomenon. Today, a shift in emphasis from a static to a dynamic approach appears to be a worthwhile change, although the design and monitoring of panel data is not simple to achieve. In our paper, we propose the usage of pseudo panels, which are less costly and easy to build with the available data for the firms. Our approach is based on a model-free technique: Dual Multi- ple Factor Analysis. The synthesis of the multivariate table is visualised on a common space that sheds light on customers’ trajectories of satisfaction. A real case study of an Italian bank is illustrated. Results related to the dynamic profiling of the clients highlights highly different behaviours that warn the management of the future trends of the services.

Most team sports are characterized by positions to which the players in a team are assigned. The goal of this classification is to attribute specific responsibilities during a game. Moreover, the same classification drives the buying and selling of players according to team managers and coaches strategies. The existing positions - often defined a long time ago - tend to reflect traditional points of view about the game and sometimes they are no longer well-suited to the new concepts arisen with the evolution of the way of playing. This paper focuses on basketball and aims at describing new roles of players during the game, by means of the analysis of players' performance statistics with data mining and machine learning tools. In detail, self-organizing maps and fuzzy clustering procedures are adopted in tandem to define groups of players with similar way of playing. The results show that, when considering the modern basketball players' statistics, classical positions are not able to fully represent their way of playing, and a new set of 5 roles emerges as a meaningful classification of players' characteristics.