Three Bartlett-type corrections for score statistics in symmetric nonlinear regression models

We present simple matrix formulae for corrected score statistics in symmetric nonlinear regression models. The corrected score statistics follow more closely a χ ² distribution than the classical score statistic. Our simulation results indicate that the corrected score tests display smaller size distortions than the original score test. We also compare the sizes and the powers of the corrected score tests with bootstrap-based score tests.     

A modified signed likelihood ratio test in elliptical structural models

In this paper we deal with the issue of performing accurate testing inference on a scalar parameter of interest in structural errors-in-variables models. The error terms are allowed to follow a multivariate distribution in the class of the elliptical distributions, which has the multivariate normal distribution as special case. We derive a modified signed likelihood ratio statistic that follows a standard normal distribution with a high degree of accuracy. Our Monte Carlo results show that the modified test is much less size distorted than its unmodified counterpart. An application is presented.     

Probabilistic evaluation of handwriting evidence: likelihood ratio for authorship

Summary.  The evaluation of handwritten characters that are selected from an anonymous letter and written material from a suspect is an open problem in forensic science. The individualization of handwriting is largely dependent on examiners who evaluate the characteristics in a qualitative and subjective way. Precise individual characterization of the shape of handwritten characters is possible through Fourier analysis: each handwritten character can be described through a set of variables such as the surface and harmonics as demonstrated by Marquis and co-workers in 2005. The assessment of the value of the evidence is performed through the derivation of a likelihood ratio for multivariate data. The methodology allows the forensic scientist to take into account the correlation between variables, and the non-constant variability within sources (i.e. individuals). Numerical procedures are implemented to handle the complexity and to compute the marginal likelihood under competing propositions.     

The impact of husband’s job loss on partners’ mental health

The objective of this paper is to examine the impact of job loss on family mental well-being. The negative income shock can affect the mental health status of the individual who directly experiences such displacement, as well as the psychological well-being of his partner; also, job loss may have a significantly detrimental effect on life satisfaction, self-esteem and on the individual’s perceived role in society. This analysis is based on a sample of married and cohabitating couples from the first 14 waves of the British Household Panel Survey. In order to correct for the possible endogeneity of job loss, data from employment histories is utilised and redundancies (different from dismissals) in declining industries are used as an indicator of exogenous job loss. Results show evidence that couples in which the husband experiences a job loss are more likely to experience poor mental health.     

Laypeople''s and Experts'' Perception of Nanotechnology Hazards

Public perception of nanotechnology may influence the realization of technological advances. Laypeople's (N=375) and experts' (N=46) perception of 20 different nanotechnology applications and three nonnanotechnology applications were examined. The psychometric paradigm was utilized and applications were described in short scenarios. Results showed that laypeople and experts assessed asbestos as much more risky than nanotechnology applications. Analyses of aggregated data suggested that perceived dreadfulness of applications and trust in governmental agencies are important factors in determining perceived risks. Similar results were observed for experts and laypeople, but the latter perceived greater risks than the former. Analyses of individual data showed that trust, perceived benefits, and general attitudes toward technology influenced the perceived risk of laypeople. In the expert sample, confidence in governmental agencies was an important predictor of risks associated with nanotechnology applications. Results suggest that public concerns about nanotechnology would diminish if measures were taken to enhance laypeople's trust in governmental agencies.     

The Management of Redundancies in Europe: The Case of Italy

The paper presents the findings of comparative and interdisciplinary legal and economic study on managing labour redundancies in seven EU member countries. It is structured for comparability between the systems examined. The introductory section contains an account of the evolution of the Italian labour market, with special reference to redundancy trends, of the features of the programmes for managing redundancies, of the roles of firms and the ‘external environment’ in handling workforce adjustments. The second section presents a map of policies that work to prevent labour redundancies (preventive measures) such as flexibility, training etc. Next, the instruments for handling temporary labour redundancies (retentive measures) are examined (e.g. short-time working, temporary layoffs etc.). The following section is devoted to instruments and programmes involved in the management of permanent labour redundancies (expulsive measures), e.g. collective dismissals, severance pay etc. The final section provides an overall assessment of the Italian system for managing labour redundancies, and briefly discusses the national debate on the prospects for reform, in light of the principles and policies of convergence set forth by the European Union.     

Multilevel IRT models for the university teaching evaluation

In this paper, a generalization of the two-parameter partial credit model (2PL-PCM) and of two special cases, the partial credit model (PCM) and the rating scale model (RSM), with a hierarchical data structure will be presented. Having shown how 2PL-PCM, as with other item response theory (IRT) models, may be read in terms of a generalized linear mixed model (GLMM) with two aggregation levels, a presentation will be given of an extension to the case of measuring the latent trait of individuals aggregated in groups. The use of this Multilevel IRT model will be illustrated via reference to the evaluation of university teaching by students following the courses. The aim is to generate a ranking of teaching on the basis of student satisfaction, so as to give teachers, and those responsible for organizing study courses, a background of information that takes the opinions of the direct target group for university teaching (that is, the students) into account, in the context of improving the teaching courses available.     

Discovering associations between players' performance indicators and matches' results in the European Soccer Leagues

The application of data mining techniques and statistical analysis to the sports field has received increasing attention in the last decade. One of the most famous sports in the world is soccer, and the present work deals with it, using data from the 2009/2010 season to the 2015/2016 season from nine European leagues extracted from the Kaggle European Soccer database. Overall performance indicators of the four roles in a soccer team (forward, midfielder, defender and goalkeeper) for home and away teams are used to investigate the relationships between them and the results of matches, and to predict the wins of the home team. The model used to answer both these demands is the Bayesian Network. This study shows that this model can be very useful for mining the relations between players'' performance indicators and for improving knowledge of the game strategies applied by coaches in different leagues. Moreover, it is shown that the ability to predict match results of the proposed Bayesian Network is roughly the same as that of the Naive Bayes model.     

Testing a Model of Trade Union Behaviour: An Application of a Multivariate Cointegration Analysis to UK Aggregate Wage Data

ABSTRACT The first part of the paper considers a behavioural model of trade unionism. Wages and employment are characterized as the outcome of a process by which the union maximizes an objective function containing wages and employment as arguments, and is constrained by a trade-off between these two variables as represented by the firm's labour demand function. In the second part, the model's equilibrium predictions for wages are estimated in the framework of a multivariate error correction model and tested for cointegration with data from Britain's manufacturing sector from 1967 to 1986.