Sample size for estimating a binomial proportion: comparison of different methods

The poor performance of the Wald method for constructing confidence intervals (CIs) for a binomial proportion has been demonstrated in a vast literature. The related problem of sample size determination needs to be updated and comparative studies are essential to understanding the performance of alternative methods. In this paper, the sample size is obtained for the Clopper–Pearson, Bayesian (Uniform and Jeffreys priors), Wilson, Agresti–Coull, Anscombe, and Wald methods. Two two-step procedures are used: one based on the expected length (EL) of the CI and another one on its first-order approximation. In the first step, all possible solutions that satisfy the optimal criterion are obtained. In the second step, a single solution is proposed according to a new criterion (e.g. highest coverage probability (CP)). In practice, it is expected a sample size reduction, therefore, we explore the behavior of the methods admitting 30% and 50% of losses. For all the methods, the ELs are inflated, as expected, but the coverage probabilities remain close to the original target (with few exceptions). It is not easy to suggest a method that is optimal throughout the range (0, 1) for p. Depending on whether the goal is to achieve CP approximately or above the nominal level different recommendations are made.     

Productivity Growth in the Lisbon Police Force

This paper estimates total productivity change with regard to the Lisbon Police Force and decomposes it into technically efficient change and technological change with data envelopment analysis (DEA). The benchmarking procedure implemented is an internal benchmarking, in which police precincts are compared against each other. The aim of this procedure is to seek out those best practices that will lead to improved performance throughout the whole force. We rank the precincts according to their total productivity change for the period 2000–2001, concluding that some precincts experienced productivity growth while a small number experienced productivity decrease. Economic implications arising from the study are considered.     

ANOVA-like analysis of matched series of studies with a common structure

It is shown how to condense the information contained in a series of studies, each constituted by an objects by variables matrix and a pair of weight matrices, into a structure vector and a sum of sums of squares of residuals. Based on this condensation we propose to carry out ANOVA-like inference for matched series of studies associated with the level combinations of some factors. It is shown how to validate the assumptions underlying the inference. An application to the results of local elections in Portugal is given.     

Deepening and widening the gap: The impacts of the COVID-19 pandemic on gender and racial inequalities in Brazil

Shaped by inconsistent policy decisions, the COVID-19 pandemic in Brazil has made structural gender and racial inequalities more acute. Black and low-income women are overburdened with unpaid domestic work, increased domestic violence, and more vulnerable due to informal and exploitative working regimes. These structural aspects are intensifying, since the pandemic has broadened inequalities at the intersection of gender, race, labor market, and social class. We examine pre- and during pandemic inequalities on three dimensions: (a) unpaid domestic and care work, (b) women's labor market participation, and (c) domestic violence. We link the care diamond model and racial stratification forwarding a feminist perspective by examining how the interlocking of race and gender in Brazil renders different socioeconomic dynamics to the detriment of Black and low-income women. Based on this evidence, we stress that a more equal future requires a better social protection and policies targeting the articulation of gender, race, and class.     

Detecting influential observations in Watson data

A method for detecting outliers in axial data has been proposed by Best and Fisher (1986 Best, D.J., Fisher, N.I. (1986). Goodness-of-fit and discordancy tests for samples from the Watson distribution on the sphere. Aust. J. Stat. 28:13–31.[Crossref] , [Google Scholar]). For extending that work, we propose four new methods. Two of them are suitable for outlier detection and they depend on the classic geodesic distance and a modified version of this distance. The other two procedures, which are designed for influential observation detection, are based on the Kullback–Leibler and Cook’s distances. Some simulation experiments are performed to compare all considered methods. Detection and error rates are used as comparison criteria. Numerical results provide evidence in favor of the KL distance.     

A new class of survival regression models with heavy-tailed errors: robustness and diagnostics

Birnbaum-Saunders models have largely been applied in material fatigue studies and reliability analyses to relate the total time until failure with some type of cumulative damage. In many problems related to the medical field, such as chronic cardiac diseases and different types of cancer, a cumulative damage caused by several risk factors might cause some degradation that leads to a fatigue process. In these cases, BS models can be suitable for describing the propagation lifetime. However, since the cumulative damage is assumed to be normally distributed in the BS distribution, the parameter estimates from this model can be sensitive to outlying observations. In order to attenuate this influence, we present in this paper BS models, in which a Student-t distribution is assumed to explain the cumulative damage. In particular, we show that the maximum likelihood estimates of the Student-t log-BS models attribute smaller weights to outlying observations, which produce robust parameter estimates. Also, some inferential results are presented. In addition, based on local influence and deviance component and martingale-type residuals, a diagnostics analysis is derived. Finally, a motivating example from the medical field is analyzed using log-BS regression models. Since the parameter estimates appear to be very sensitive to outlying and influential observations, the Student-t log-BS regression model should attenuate such influences. The model checking methodologies developed in this paper are used to compare the fitted models.     

Musculoskeletal disorders and psychosocial risk factors among workers of the aircraft maintenance industry

During the recent decades Brazil has experienced an exponential growth in the aviation sector resulting in an increasing workforce. The aircraft maintenance industry stands out, where the workers have to handle different kind of objects. The aim of this study was to evaluate psychosocial indicators as well as musculoskeletal symptoms and disorders among aircraft maintenance workers. One hundred and one employees were evaluated (32.69 ± 8.25 yr, 79.8 ± 13.4 kg, and 1.75 ± 0.07 m). Musculoskeletal symptoms and disorders were assessed through the Nordic Musculoskeletal Questionnaire (NMQ) and a standardized physical examination. The Job Content Questionnaire (JCQ) and the Utrecht Work Engagement Scale (UWES) were applied to evaluate psychosocial indicators. Results of the NMQ indicate the lower back as the most affected body region. On the other hand, the physical examination has shown clinical diagnosis of shoulder disorders. Neck, upper back and ankle/foot were also reported as painful sites. Most of workers have active work-demand profile and high work engagement levels. We suggest that musculoskeletal symptoms may be related to high biomechanical demand of the tasks performed by workers, what must be further investigated.