Building a System of Indicators to Evaluate the Right of a Child to Play

This study presents the results of a research project whose objective is to propose measures to evaluate the right of children to engage in play, as recognised in the Convention on the Rights of the Child. After exhausting documentation and statistical sources, a lack of measures related to this right was clear. This led to the formation of discussion groups about play with schools, families and social agents. From this, an initial matrix was developed and submitted to experts who selected the most suitable measures. This resulted in the SIDERJU matrix, composed of measures for the structure, process and result.     

Robust inference for the stress–strength reliability

We address the problem of robust inference about the stress–strength reliability parameter R = P(X < Y), where X and Y are taken to be independent random variables. Indeed, although classical likelihood based procedures for inference on R are available, it is well-known that they can be badly affected by mild departures from model assumptions, regarding both stress and strength data. The proposed robust method relies on the theory of bounded influence M-estimators. We obtain large-sample test statistics with the standard asymptotic distribution by means of delta-method asymptotics. The finite sample behavior of these tests is investigated by some numerical studies, when both X and Y are independent exponential or normal random variables. An illustrative application in a regression setting is also discussed.     

Migration and the Currency Denomination of Trade

Using a large, transaction‐level dataset of Italian exports and imports with non‐European Union countries, we assess the role of migrants’ networks in shaping the currency denomination of trade. Our results, new to the literature, show sizable, significant effects of migration on the currency denomination of trade. Generally, more migrants lead to more invoicing in the exporter's and importer's currency relative to a vehicle currency, higher educated migrants increase invoicing in the exporter's and importer's currency relative to a vehicle currency, and Italian migrants living in foreign countries have a greater impact relative to foreign migrants living in Italy.     

The decline of motivation?: From commitment to dropping out of volunteering

This article studies volunteerism through the phenomenon of dropping out. By ascertaining the achievements, difficulties, and dilemmas of volunteers at the Center for Assistance to Victims of Sexual Assault and Domestic Violence, we explored the process of dropping out as an encore to understanding the meaning of volunteerism that ends with abandoning a desired activity. On the basis of a longitudinal study, we argue that dropping out is not always a product of waning motivation—for many volunteers, dropping out was extremely difficult—but rather the outcome of unabridged discrepancies between “ought” and “actual” experiences. Volunteers expect to feel good about themselves. In contrast, the organization expects them to act as free agents who can independently manage feelings of pain and self‐doubt. When such discrepancies between expectations and reality occur, feelings of anger and disappointment set in. As a result, devoted volunteers drop out in order to preserve their positive self‐feeling. It is our contention that in order to understand the nature of volunteers' dropout and perseverance, close attention should be paid to processes of self‐regulation in the context of the specific relations between the volunteers and the organization.     

Formación militar y dictadura: Un enfoque psicológico

Resumen

Pocos estudios se han centrado en analizar la importancia que la situación laboral de las personas tiene en el proceso de percepción de impresiones en el contexto social de escasez de empleo. Este estudio aborda el fenómeno de la formación de impresiones a partir del experimento de Asch utilizando como rasgos centrales “empleada”, “desempleada” y “jubilada” y los rasgos respuesta del experimento original. La muestra se compuso de 239 estudiantes universitarios sin conocimientos previos del experimento de Ach. Se utilizó un diseño experimental unifactorial (situación laboral) multicondicional (rasgos respuesta) de grupos distintos de sujetos. Mediante pruebas chi cuadrado, los resultados obtenidos mostraron que la persona “empleada” fue descrita como más importante y perseverante que la “desempleada”, pero más egoísta que la “jubilada”. La persona “desempleada” fue considerada como la más triste, y junto con la persona “jubilada” más sociables en comparación con la “empleada”. Las personas poderosas—entendiendo el trabajo como fuente de poder y estatus—fueron percibidas como competentes pero poco sociables, dentro del marco del Modelo sobre el Contenido Mixto de los Estereotipos de Fiske et al.     

Statistical inference for the effect of magnetic brain stimulation on a motoneurone

A stochastic model is developed for the possible excitatory and inhibitory effects of a stimulus to the brain on the activity of single human motoneurones. The model consists of a Wiener process for the build-up of underlying potential, a deterministic effect due to the stimulus and a random lag from brain to muscle. Direct likelihood inference for its parameters seems impossible, and we study the use of simulation to estimate the log-likelihood for the parameters of substantive interest. Monte Carlo methods yield point and confidence interval estimates of the membrane excitability underlying excitatory and inhibitory effects. The main qualitative conclusion is that both excitatory and inhibitory effects are unambiguously present. The contribution of statistical analysis to this problem is to provide accurate and apparently reliable inference for the quantities of neurophysiological interest. More generally, our methodology has the potential to make accurate likelihood-based inferences in challenging problems, but the computational burden can be large, particularly if the model is not fully adequate for the data, as in our application.     

Bounded Estimation in the Presence of Nuisance Parameters

The aim of this paper is to extend in a natural fashion the results on the treatment of nuisance parameters from the profile likelihood theory to the field of robust statistics. Similarly to what happens when there are no nuisance parameters, the attempt is to derive a bounded estimating function for a parameter of interest in the presence of nuisance parameters. The proposed method is based on a classical truncation argument of the theory of robustness applied to a generalized profile score function. By means of comparative studies, we show that this robust procedure for inference in the presence of a nuisance parameter can be used successfully in a parametric setting.     

Non-parametric bootstrap recycling

The double bootstrap provides diagnostics for bootstrap calculations and, if need be, appropriate adjustments. The amount of computation involved is usually considerable, and recycling provides a less computer intensive alternative. Recycling consists of using repeatedly the same samples drawn from a recycling distribution G for estimation under each first-level bootstrap distribution, rather than independently repeating the simulation and estimation steps for each of these.Recycling is successful in parametric applications of the bootstrap, as demonstrated by M.A. Newton and C.J. Geyer (J. Amer. Statist. Assoc. 89: 905–912, 1994). We show that it is bound to fail in non-parametric bootstrap applications, and suggest a modification that makes the method work. The modification consists of smoothing the first-level bootstrap distributions, with the desired consequence that this removes the zero probabilities in the multinomial distributions that define them. We also discuss efficient choices of recycling distributions, both in terms of estimator efficiency and simulation efficiency.     

A note on empirical likelihoods derived from pairwise score functions

Pairwise likelihood functions are convenient surrogates for the ordinary likelihood, useful when the latter is too difficult or even impractical to compute. One drawback of pairwise likelihood inference is that, for a multidimensional parameter of interest, the pairwise likelihood analogue of the likelihood ratio statistic does not have the standard chi-square asymptotic distribution. Invoking the theory of unbiased estimating functions, this paper proposes and discusses a computationally and theoretically attractive approach based on the derivation of empirical likelihood functions from the pairwise scores. This approach produces alternatives to the pairwise likelihood ratio statistic, which allow reference to the usual asymptotic chi-square distribution and which are useful when the elements of the Godambe information are troublesome to evaluate or in the presence of large data sets with relative small sample sizes. Two Monte Carlo studies are performed in order to assess the finite-sample performance of the proposed empirical pairwise likelihoods.