Social Psychology in Mexico: A Fifteen-Year Review

This article reviews the development of social psychology in Mexico by summarizing major trends in the field and their representation in La Psicología Social en México [Social Psychology in Mexico] and in the Revista de Psicología Social y Personalidad [Journal of Social Psychology and Personality], both published by the Asociacion Mexicana de Psicologia Social [Mexican Association of Social Psychology, AMEPSO] between 1986 and 1998. Over the years, the Mexican Association of Social Psychology has facilitated the professional advancement of many psychologists, whose diverse research areas include applied psychology, environmental psychology, social psychology, cognitive psychology, Mexican ethnopsychology, developmental psychology, ecological psychology, personality, and gender relations. Special emphasis is placed on the discussion of the current state of psychological methodology in Mexico and the importance of designing culturally relevant instruments.     

Moving communities: A process of negotiation with a Gypsy minority for empowerment

This paper describes the process by which the relationship between university workers and members of a Gypsy community evolved. Transformation in the relationships between the two, in terms of knowledge, trust, and affect, in turn transformed the nature of the work undertaken. What started as research on the community changed into research within and of the community. The process is discussed in terms of empowerment, community psychological practice and participatory action research. Este artículo describe el proceso de cambio de la relación establecida entre miembros de una universidad y miembros de una comunidad gitana. Las transformaciones que dicha relación experimentó, en términos de conocimiento, confianza y afecto, acabaron alterando la naturaleza del propio proyecto. Lo que empezó siendo una investigación sobre una comunidad, fue transformándose en una investigación en la comunidad, con la colaboración de la comunidad. El artículo discute este proceso se discute en términos de 'empowerment', psicología comunitaria, e investigación-acción.     

Social Capital and Subjective Wellbeing in Europe: A New Approach on Social Capital

This paper aims to analyze the relationship between the various dimensions of social capital and subjective wellbeing. Data used in this study come from the fourth wave of the European Social Survey and different measures of wellbeing are used to take account of both the cognitive and affective processes of individual wellbeing (i.e. life satisfaction, happiness, and subjective wellbeing). A factor analysis is performed to summarize information coming from a large set of variables into different components corresponding to each dimension of social capital (i.e. networks, norms, and trust). Among the results, we find that the impact of social capital on subjective wellbeing differ depending on the component of social capital which is under analysis. In particular, social networks, social trust and institutional trust are the components that show a higher correlation with subjective wellbeing. Furthermore, in addition to the positive effects of the individual variables, our results suggest that social capital at the aggregate level positively correlates with individual wellbeing, thus pointing to an external or environmental effect of social capital.     

Adaptive PORT–MVRB estimation: an empirical comparison of two heuristic algorithms

In this article, we deal with an empirical comparison of two data-driven heuristic procedures of estimation of a positive extreme value index (EVI), working thus with heavy right tails. The semi-parametric EVI-estimators under consideration, the so-called peaks over random threshold (PORT)–minimum-variance reduced-bias (MVRB) EVI-estimators, are location and scale-invariant estimators, based on the PORT methodology applied to second-order MVRB EVI-estimators. Trivial adaptations of these algorithms make them work for a similar estimation of other parameters of extreme events, such as the Value-at-Risk at a level p, the expected shortfall and the probability of exceedance of a high level x, among others. Applications to simulated data sets and to real data sets in the field of finance are provided.     

A bootstrap test for single index models

Single index models are frequently used in econometrics and biometrics. Logit and Probit models arc special cases with fixed link functions. In this paper we consider a bootstrap specification test that detects nonparametric deviations of the link function. The bootstrap is used with the aim to rind a more accurate distribution under the null than the normal approximation. We prove that the statistic and its bootstrapped version have the same asymptotic distribution. In a simulation study we show that the bootstrap is able to capture the negative bias and the skewness of the test statistic. It yields better approximations to the true critical values and consequently it has a more accurate level than the normal approximation.     

PROMETHEE IV through kernel density estimation

ABSTRACT

This paper presents a new version of PROMETHEE IV, which considers the empirical distribution of the criteria through kernel density estimation to evaluate alternatives. The developed method has the ability to treat criteria according to their distribution. The classic PROMETHEE IV can produce divergent integrals, and this could be the cause for its insufficient exploration in literature. The proposed method overcomes this situation since large values have little weight compared to values near the mean.     

Estimating and Validating Nonlinear Regression Metamodels in Simulation

Frequently, the main objective of statistically designed simulation experiments is to estimate and validate regression metamodels, where the regressors are functions of the design variables and the dependent variable is the system response. In this article, a weighted least squares procedure for estimating the unknown parameters of a nonlinear regression metamodel is formulated and evaluated. Since the validity of a fitted regression model must be tested, a method for validating nonlinear regression simulation metamodels is presented. This method is a generalization of the cross-validation test proposed by Kleijnen (1983 Kleijnen , J. P. C. ( 1983 ). Cross-validation using the t statistic . European Journal of Operational Research 13 : 133 – 141 .[Crossref] , [Google Scholar]) in the context of linear regression metamodels. One drawback of the cross-validation strategy is the need to perform a large number of nonlinear regressions, if the number of experimental points is large. In this article, cross-validation is implemented using only one nonlinear regression. The proposed statistical analysis allows us to obtain Scheffé-type simultaneous confidence intervals for linear combinations of the metamodel's unknown parameters. Using the well-known M/M/1 example, a metamodel is built and validated with the aid of the proposed procedure.     

A new mathematical approach for the estimation of the AUC and its variability under different experimental designs in preclinical studies

The aim of the present work was to develop a new mathematical method for estimating the area under the curve (AUC) and its variability that could be applied in different preclinical experimental designs and amenable to be implemented in standard calculation worksheets. In order to assess the usefulness of the new approach, different experimental scenarios were studied and the results were compared with those obtained with commonly used software: WinNonlin® and Phoenix WinNonlin®. The results do not show statistical differences among the AUC values obtained by both procedures, but the new method appears to be a better estimator of the AUC standard error, measured as the coverage of 95% confidence interval. In this way, the new proposed method demonstrates to be as useful as WinNonlin® software when it was applicable. Copyright © 2011 John Wiley & Sons, Ltd.