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We would like to note the following corrections to the original version of Gelo et al.: In the Section Method, the sentence: “(The team of judges was composed of the second [X.X.], third [X.X.], fourth [X.X.], and fifth [X.X.] author of the present manuscript. The auditors were the first [X.X.X.X.] and sixth [X.X.] author of the present article.) [Initials have been omitted for anonymity reasons. They will be added in case of publication.]” should be.

Impairments in mentalizing abilities are thought to account for the high aggressive tendencies observed among individuals with pathological personality. However, the question of whether mentalizing impairments may mediate the pathways by which pathological personality leads to aggression has not yet been answered. This study first investigated the psychometric proprieties of the Italian version of the Reflective Functioning Questionnaire (RFQ). Then, we tested the mediating role of mentalizing in the relationship between the three pathological personality domains and aggressiveness. The study was conducted on a sample of 327 participants includinggroup of violent offenders (n=118) and a group of community participants (n=209). All subjects fulfilled the RFQ, the Personality Inventory for DSM-5 (PID-5) and the Aggression Questionnaire (AQ). Partial Least Squares–Path Modelling with higher-order construct definition was used. Mentalizing capacities were shown to significantly mediate the pathways leading some pathological personality traits to aggression. Data supported the factorial structure of the RFQ found in the original validation study. Results also support the existence of a second-order variable, mentalizing, resulting from the convergence of hypomentalizing and hypermentalizing, Psychology Hub, Vol 38, No 1 (2021)

The accuracy of the ALS procedure for fitting the CP decomposition is affected by incorrect model selection due to the properties of its objective function. A study on ALS performance is presented in order to show that for large data sets this occasional shortcoming becomes prevalent. This deficiency should warn off researchers from employing ALS unless the rank of the underlying trilinear structure can be established in advance. Multi-optimization provides a possible solution: ALS can be initialized with procedures insensitive to over-factoring such as SWATLD and ATLD. In this manner it is possible to overcome factorization issues and provide a gain in efficiency without relying on computationally expensive model selection procedures.

Research on job crafting is increasing nowadays. Job crafting has been studied in terms of a mediator variable useful to improve positive organizational behaviors, and it has crucial theoretical and practical implications. In order to facilitate its measurement in large surveys, in different settings, we aimed to develop a brief 12-item version, the Job Crafting Scale-Short Form (JCS-SF). Having a brief scale to measure job crafting behaviors will contribute to facilitate research in several organizational contexts. This study presents the main psychometric properties of a brief JC scale based on JC scale developed by Tims et al. (2012). EFA results show support for the original Four-factor solution. Results have been confirmed using CFA. The four subscales showed adequate reliability. The brief scale could be used for researchers and practitioners in public and private organizational sectors.

In the last years, the scientific interest on job crafting within the Job demands-resources theory has been increased. The paper aimed to examine the role of job crafting in the relationship between self-efficacy and performance at work. Based on Job demands-resources theory, we hypothesized that employees with higher levels of self-efficacy would be most likely to make proactively changes in their own jobs in order to perform well. Specifically, we hypothesized that job crafting may mediate the positive effects between self-efficacy and work performance and organizational citizenship behaviours. Participants were 361 employees of different Italian organizations. Results from SEM showed the positive effect of self-efficacy on job crafting, work performance, and organizational citizenship behaviours. Furthermore, job crafting partially mediated the relationship between self-efficacy and work performance and totally mediated the relationship between self-efficacy and organizational citizenship behaviours. Findings suggest that job crafting can play a crucial role in the influence of personal resources, as self-efficacy, and the performance at work. Findings suggest that job crafting can play a crucial role in the influence of personal resources, as self-efficacy, and the performance at work.

The focus of this paper is on spatial structural equation models (S-SEM) also extended to a Panel data framework. More specifically, our objective is to introduce a generalized maximum entropy formulation for the class of S-SEM with the aim of developing a composite index. We present an application of the method to real data finalized to investigatedynamicsandcomplexinteractionsbetweensomeselecteddimensionsthatrepresentthe mainmeasuresofintangibleassetsforapanelofOECDcountriesovertheperiod1998–2008.

The paper intends to introduce some methodological evolutions in the field of Customer Satisfaction (CS) regards the following aspects: the uni-dimensionality evaluation of questionnaire, considering the Simple Component Analysis (SCA); the parameters estimation of Structural Equation Model (SEM), based on the Generalized Maximum Entropy (GME) method; the detection of relationship between categorical variables, in the framework of Non Symmetrical Correspondence Analysis (NSCA).

Le emissioni del traffico veicolare rappresentano un'importante fonte di inquinamento nelle città. Queste emissioni sono costituite da miscele di varie sostanze, alcune delle quali rappresentano un grosso problema per gli effetti dannosi che possono avere nei confronti della nostra salute e ell'ambiente in cui viviamo. La necessità di ridurre questo fenomeno ha portato all'introduzione di una serie di direttive che pongono delle limitazioni lla quantità di sostanze inquinanti emesse dagli autoveicoli. Gli amministratori locali sono, quindi, obbligati dalle leggi vigenti a valutare in maniera previsionale l'impatto ambientale del sistema traffico e ad intervenire con misure opportune -"blocco totale o parziale del traffico"- per evitare il uperamento delle soglie d'allarme di inquinamento dell'aria. In tale contesto emerge la domanda di strumenti quantitativi capaci di valutare in maniera previsionale l'impatto, in termini di emissioni inquinanti, prodotte da specifiche famiglie (o categorie) di mezzi di trasporto, in relazione a redeterminate situazioni traffico/strada.

The objective of this paper is to develop a GME formulation for the class of spatial structural equations models (S-SEM). In this respect, two innovatory as- pects are introduced: (i) the formalization of the GME estimation approach for the spatial structural equations models which accounts for spatial heterogeneity and spa- tial dependence; (ii) the extension of the methodology to a panel data framework. We also present an application of the method to real data finalized to investigate dispari- ties of unemployment rates in OECD countries over the period 1998-2006.

Applications of partial least squares structural equation modelling (PLS-SEM) often draw on survey data. While researchers go to great lengths to document reliability and validity statistics that support the generalisability of their findings, they often overlook or ignore a more fundamental issue related to data analysis—the representativeness of their sample. Addressing this concern, the present paper offers guidelines for using the weighted PLS-SEM (WPLS-SEM) algorithm to apply sampling weights in the model estimation. The results of the WPLS algorithm and the traditional PLS algorithm are then compared using a marketing research model. The findings show that researchers should routinely consider the procedure of the WPLS algorithm when using the PLS technique for assessment. The WPLS algorithm is a useful and practical approach for achieving better average population estimates in situations where researchers have a set of appropriate weights. This paper substantiates the use of the WPLS algorithm and provides business researchers and practitioners with the proper guidelines to assess, report, and interpret PLS-SEM results. It also illustrates that the use of the WPLS algorithm produces different inference test results in the structural model and different predictive relevance results. Thus, the study contributes to the advancement of PLS-SEM applications.

We propose a new method to combine adaptive processes with a class of entropy estimators for the case of streams of data. Starting from a first estimation obtained from a batch of initial data, model parameters are estimated at each step by combining the prior knowledge with the new observation (or a block of observations). This allows to extend the maximum entropy technique to a dynamical setting, also distinguishing between entropic contributions of the signal and the error. Furthermore, it provides a suitable approximation of standard GME problems when the exacted solutions are hard to evaluate. We test this method by performing numerical simulations at various sample sizes and batch dimensions. Moreover, we extend this analysis exploring intermediate cases between streaming GCE and standard GCE, i.e. considering blocks of observations of different sizes to update the estimates, and incorporating collinearity effects as well. The role of time in the balance between entropic contributions of signal and errors is further explored considering a variation of the Streaming GCE algorithm, namely, Weighted Streaming GCE. Finally, we discuss the results: in particular, we highlight the main characteristics of this method, the range of application, and future perspectives., Comment: 22 pages, 11 figures

This work focuses on consumer evaluation of bluefish products in terms of three distinguished investigation macro-dimensions: Consumer habits, Bluefish Perception, New Product Propensity. We analyse data to extract the contributions of variables in these macro-dimensions and discuss the phenomena of uncertainty and factor indeterminacy in their relevance as drivers of consumers' decisions.

Three main methodological practices have been employed in psychotherapy science: the empirical-quantitative, empirical-qualitative, and theoretical one. Some scholars have argued for a monopoly of the empirical-quantitative methodological practice, sustained by scientific monism. This systematic review aims at exploring the contribution of each methodological practice to the field. Fifteen journals were searched from 2003 to 2013. A total of 9796 publications and 9915 studies met inclusion criteria and were coded for the methodological practice employed. Empirical-quantitative studies were the most published overall, over time, and in most of the journals considered. This overwhelming prevalence increased when considering the citation rates of the publications. We argue that these results are indicative of a quantitative monopoly, which in turn is due to a lack of critical thinking sustaining scientific monism. We call for disciplinary critical thinking and the consequent scientific pluralism valuing the plurality, diversity, and multiplicity of all the existing methodological practices.

To illustrate a new technological advance in the standard drug-induced sleep endoscopy (DISE) model, a new machine was used, the Experimental 5 Video Stream System (5VsEs), which is capable of simultaneously visualizing all the decisional parameters on a single monitor, and recording and storing them in a single uneditable video. The DISE procedure was performed on 48 obstructive sleep apnea (OSA) or snoring patients. The parameters simultaneously recorded on a single monitor are (1) the pharmacokinetics and pharmacodynamics of propofol (through the target controlled infusion (TCI) pump monitor), (2) the endoscopic upper airway view, (3) the polygraphic pattern, and (4) the level of sedation (through the bispectral index (BIS) value). In parallel to the BIS recording, the middle latency auditory evoked potential (MLAEP) was also recorded and provided. Recorded videos from the 5VsEs machine were re-evaluated six months later by the same clinician and a second clinician to evaluate the concordance of the therapeutic indications between the two. After the six-month period, the same operator confirmed all their clinical decisions for 45 out of 48 videos. Three videos were no longer evaluable for technical reasons, so were excluded from further analysis. The comparison between the two operators showed a complete adherence in 98% of cases. The 5VsEs machine provides a multiparametric evaluation setting, defined as an &ldquo, all in one glance&rdquo, strategy, which allows a faster and more effective interpretation of all the simultaneous parameters during the DISE procedure, improving the diagnostic accuracy, and providing a more accurate post-analysis, as well as legal and research advantages.

This chapter is an extended version of the paper: Salvatore et al. (2018a). Symbolic universes between present and future of Europe. First results of the map of European societies’ cultural milieu. PLoS ONE 13(1): e0189885. With respect to that work, the current chapter presents an extension of the levels of analysis (i.e. the detection of the lines of semiotic force) and a more comprehensive sample (i.e. the inclusion of Dutch and Danish subsamples).; International audience; The chapter reports the main findings of an analysis of cultural milieus of a sample of 11 European countries (Cyprus, Denmark, Estonia, France, Germany, Greece, Italy, Malta, Netherlands, Spain, United Kingdom). The analysis is based on a questionnaire (View of Context—VOC) applied to a sample built through a two-step procedure of post-hoc random selection from a broader dataset based on an online survey. According to the methodological framework outlined in the previous chapter, responses to the questionnaire were subjected to multidimensional analysis—a combination of Multiple Correspondence Analysis and Cluster Analysis. We identified three fundamental dimensions of meanings, interpreted as lines of semiotic forces comprising the semiotic field of European societies: Affective connotation of the world—foe versus friend; Direction of desire—passivity versus engagement; Form of demand—demand for systemic resources versus demand for community bond. Moreover, 5 symbolic universes were mapped. Each symbolic universe corresponds to a basic, embodied, affect-laden, generalized worldview: People in this study see the world as either (a) an ordered universe; (b) a matter of interpersonal bond; (c) a caring society; (d) consisting of a niche of belongingness; (e) a hostile place (others’ world).

In medical emergency situations, the triage process allows patients in potentially life-threatening condition to receive the fastest and most appropriate medical treatment. Triage consists in an evaluation of patients’ medical condition on a colour-based scale, reflecting from major to minor urgency. Shannon’s entropy measures are applied to such process in order to evaluate concordance, overestimation and underestimation of triage codes assigned to patients in two different moments and by different health-care professionals: during the acceptance phase, by nurses (variable X), and by physicians after deepened diagnostic evaluation (variable Y). Entropy indexes were also used to compare the years 2016 and 2015, showing a little increment of equivocal transmission with respect to year 2015.

In this paper we present a way of constructing design of experiments by Multivariate Additive Partial Least-Squares Splines, in short MAPLSS. Trying to select the most informative model based on an as small as possible training data set, we process an adaptive incremental selection of observations by a particular bootstrap procedure. Why MAPLSS models? Because they inherit the advantages of the boosted PLS regression that permits to capture additively non-linear main effects and relevant interactions in the difficult framework of small training sets. The effectiveness of this approach is illustrated on the reservoir simulator data used to forecast oil production.

Traditionally multiple correspondence analysis involves transforming a contingency table to its indicator or Burt matrix form then performing the classical two-way approach. Alternatively, one may also consider techniques that are more model based such as the partitions associated with the PARAFAC/CANDECOMP models or the Tucker3 model. Traditionally these procedures have proven to be of benefit in studies where the variables are nominally structured. This paper will demonstrate how they can be adapted for ordinal variables by incorporating orthogonal polynomials into the partitions and a graphical description of the association can be obtained by considering correspondence analysis. This paper will also consider the case where the variables of a three-way contingency table are asymmetrically associated.

Arbitrage Pricing Theory (APT) leads good estimates of expected utility stock returns by means of k factors. Notwithstanding initial skepticism the idea of using multiple risk factors to explain the relationship between expected return and asset risk has been winning. In literature the APT has been seen as a generalization of single risk factor approach of Capital Asset Pricing Model (CAPM). The APT provides a better indication of asset risk and a better estimate of expected return than CAPM does. In this paper we propose a generalization of APT to non-linear case. In order to study the relationships which occur between return and multiple risk factors, we propose non-linear principal components. To find justifications for embracing a more complicated model than traditional APT we evaluate the consistency of results by known real data.

Nello studio dei fenomeni reali, spesso ci si trova ad analizzare dati che hanno una struttura gerarchica. Nei problemi di valutazione della performance dei servizi alla persona di pubblica utilità (sanità, formazione, sociale, etc.) lo studio delle relazioni/associazioni tra le unità semplici e i gruppi di appartenenza è particolarmente interessante ed informativo. Il concetto generale è che gli individui interagendo con l’ambiente, risultano influenzati nelle loro scelte o nel loro modo di reagire a stimoli, dal gruppo sociale o dal contesto a cui appartengono (Hox, 2002). Le variazioni negli atteggiamenti degli individui (preferenze, propensioni all’acquisto, soddisfazione), quindi, non dipenderanno solo dalle variabili misurate sugli stessi, ma anche dall’influenza che il contesto ha su di loro. In letteratura sono proposte diverse strategie di analisi per dati con struttura di tipo gerarchico. Distinguiamo le tecniche inferenziali come i modelli regressivi multilivello (Bryk & Raudenbush, 1992; Goldstein, 1987; Longford, 1986; Aitkin, 1981), dalle tecniche esplorative di analisi dei dati come l’Analisi in Componenti Principali non lineare gerarchica (Michealidis & de Leeuw, 2000, Gallo & Lombardo, 2001; Lombardo & Gallo 2004). Il presente lavoro si inquadra tra le tecniche di analisi multidimensionale dei dati e si basa sull’algoritmo NIPALS (Non-linear Iterative Partial Least Squares, Wold, 1966) che consente la stima di componenti principali lineari. L’idea principale è di analizzare i dati evidenziando l’influenza che i gruppi hanno sul contesto generale, così come la dipendenza di ciascun gruppo dal contesto. La metodologia proposta è illustrata mediante l’uso di un data set utilizzato per misurare la soddisfazione di pazienti ricoverati presso l’istituto ospedaliero dell’Universitet di Linkoping in Svezia (Krevers 2002). I dati presentano una struttura gerarchica a due livelli: i pazienti e i reparti di degenza.