The Rationality of Under‐employing the Best‐performing Soccer Players

Abstract. This paper analyses the influence of sport performance (productivity) and other variables measuring the economic contribution of soccer players, upon the coach's decision of selecting a particular player. Using as dependent variable the proportion of time that individuals play in the Spanish professional soccer league, the paper concludes that players' economic market value does significantly affect the coach's choice, revealing the existence of other aims different from maximizing sport performance. We also examine the type of discrimination associated with lower chances of playing, which leads to smaller earnings and poorer career opportunities. The empirical evidence does not support discrimination due to nationality.     

Monitoring correlation change in a sequence of random variables

We propose a monitoring procedure to test for the constancy of the correlation coefficient of a sequence of random variables. The idea of the method is that a historical sample is available and the goal is to monitor for changes in the correlation as new data become available. We introduce a detector which is based on the first hitting time of a CUSUM-type statistic over a suitably constructed threshold function. We derive the asymptotic distribution of the detector and show that the procedure detects a change with probability approaching unity as the length of the historical period increases. The method is illustrated by Monte Carlo experiments and the analysis of a real application with the log-returns of the Standard & Poor's 500 (S&P 500) and IBM stock assets.     

On the Strong Consistency of Ridge Estimates

In this article, we establish strong consistency of the ridge estimates using extended results for the strong consistency of the least squares estimates in multiple regression models which discard the usual assumption of null mean value for the errors and only requires them to be i.i.d. with absolute moment of order r (0 < r ? 1).     

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.     

Pivotal Quantities Based on Sequential Data: A Bootstrap Approach

A bootstrap algorithm is provided for obtaining a confidence interval for the mean of a probability distribution when sequential data are considered. For this kind of data the empirical distribution can be biased but its bias is bounded by the coefficient of variation of the stopping rule associated with the sequential procedure. When using this distribution for resampling the validity of the bootstrap approach is established by means of a series expansion of the corresponding pivotal quantity. A simulation study is carried out using Wang and Tsiatis type tests and considering the normal and exponential distributions to generate the data. This study confirms that for moderate coefficients of variation of the stopping rule, the bootstrap method allows adequate confidence intervals for the parameters to be obtained, whichever is the distribution of data.     

A General Class of Estimators for the Linear Regression Model Affected by Collinearity and Outliers

In this article, a general class of estimators for the linear regression model affected by outliers and collinearity is introduced and studied in some detail. This class of estimators combines the theory of light, maximum entropy, and robust regression techniques. Our theoretical findings are illustrated through a Monte Carlo simulation study.     

Optimal Design of Acceptance Sampling Plans by Variables for Nonconforming Proportions When the Standard Deviation Is Unknown

This article presents an optimization-based approach for the design of acceptance sampling plans by variables for controlling nonconforming proportions when the standard deviation is unknown. The variables are described by rigorous noncentral Student’s t-distributions. Single and double acceptance sampling (AS) plans are addressed. The optimal design results from minimizing the average sampling number (ASN), subject to conditions holding at producer’s and consumer’s required quality levels. The problem is then solved employing a nonlinear programming solver. The results obtained are in close agreement with previous sampling plans found in the literature, outperforming them regarding the feasibility.     

Modeling the impact of social discrimination on the physical and mental health of Portuguese gay,lesbian and bisexual people

Background: Despite growing acceptance of same-sex sexuality in Portugal, identity development of lesbian, gay and bisexual (LGB) individuals is still restricted by negative societal attitudes, which maintain the experience of stigmatization and discrimination. The purpose of this study is to document the frequency of discriminatory events experienced by sexual minorities and their association with indicators of physical and mental health in Portugal. Methods: A total of 610 LGB participants completed an online survey (mean age?=?34.48, SD?=?11.54). Most participants were single and self-identified as gay (73.8%). The survey included five categories of survey items: demographic information, social support, physical health, mental health, and discrimination experiences. Results: Physical and mental health results revealed that bisexual people were more likely to report higher levels of psychological distress than gay men. Overall, between one-fifth and one-fourth of the participants in this sample frequently felt the need to hide their sexual orientation to prevent discrimination experiences across the different settings. Regarding actual discrimination experiences, close to 20% reported having suffered from verbal abuse, followed by close to 10% who suffered from written threats, harassment, and physical threats. A hierarchical multiple regression analysis was performed to assess the effects of anticipated and actual discrimination on mental health. Possible confounding variables were added in the first block – age, sexual orientation, being in a relationship, body mass index, and HIV status. Anticipated and actual discrimination experiences were added in the second block. The first block of the analysis explained 6% of the overall variance, while the second block – discrimination experiences – explained an additional 17%. Conclusion: Portuguese culture and stigma/discrimination create discriminatory experiences which impact LGB people's health. Unless policies are changed to allow for the acceptance of LGB people, they will continue to experience violence and discrimination as a result of homophobia.