Abstract Poisson distribution is a popular discrete model used to describe counting information, from which traditional control charts involving count data, such as the c and u charts, have been established in the literature. However, several studies recognize the need for alternative control charts that allow for data overdispersion, which can be encountered in many fields, including ecology, healthcare, industry, and others. The Bell distribution, recently proposed by Castellares et al. (2018), is a particular solution of a multiple Poisson process able to accommodate overdispersed data. It can be used as an alternative to the usual Poisson (which, although not nested in the Bell family, is approached for small values of the Bell distribution) Poisson, negative binomial, and COM-Poisson distributions for modeling count data in several areas. In this paper, we consider the Bell distribution to introduce two new exciting, and useful statistical control charts for counting processes, which are capable of monitoring count data with overdispersion. The performance of the so-called Bell charts, namely Bell-c and Bell-u charts, is evaluated by the average run length in numerical simulation. Some artificial and real data sets are used to illustrate the applicability of the proposed control charts.

Resumen En este artículo, discutimos varias propiedades matemáticas y métodos de estimación para una versión reparametrizada de la distribución ponderada de Lindley (RWL). La distribución RWL puede ser particularmente útil para modelar datos de confiabilidad (supervivencia) con función de tasa de riesgo en forma de bañera o creciente. El procedimiento inferencial para obtener las estimaciones de los parámetros se realiza mediante el enfoque de máxima verosimilitud considerando la censura aleatoria a la derecha. Se realizan extensas simulaciones numéricas para investigar y evaluar el rendimiento del método de estimación propuesto. Finalmente, la utilidad del modelo RWL se analiza mediante el uso de dos conjuntos de datos reales.

Abstract In this paper, we discuss several mathematical properties and estimation methods for a reparameterized version of the weighted Lindley (RWL) distribution. The RWL distribution can be particularly useful for modeling reliability (survival) data with bathtub-shaped or increasing hazard rate function. The inferential procedure to obtain the parameter estimates is conducted via the maximum likelihood approach considering random right-censoring. Extensive numerical simulations are carried out to investigate and evaluate the performance of the proposed estimation method. Finally, the potentiality of the RWL model is analyzed by employing two real data sets.

Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model, a logistic regression with state-dependent sample selection model and a bounded logistic regression model via a large simulation study. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian retail bank portfolio. Our simulation results so far revealed that there is nostatistically significant difference in terms of predictive capacity among the naive logistic regression models, the logistic regression with state-dependent sample selection models and the bounded logistic regression models. However, there is difference between the distributions of the estimated default probabilities from these three statistical modeling techniques, with the naive logistic regression models and the boundedlogistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. Which are common in practice.

Background: Low back pain (LBP) and urinary incontinence (UI) are highly prevalent among elderly individuals. In young adults, changes in trunk muscle recruitment, as assessed via ultrasound imaging, may be associated with lumbar spine stability. Objective: To assess the associations between LBP, UI, and the pattern of transversus abdominis (TrA), internal (IO), and external oblique (EO) muscle recruitment in the elderly as evaluated by ultrasound imaging. Method: Fifty-four elderly individuals (mean age: 72±5.2 years) who complained of LBP and/or UI as assessed by the McGill Pain Questionnaire, Incontinence Questionnaire-Short Form, and ultrasound imaging were included in the study. The statistical analysis comprised a multiple linear regression model, and a p-value <0.05 was considered significant. Results: The regression models for the TrA, IO, and EO muscle thickness levels explained 2.0% (R2=0.02; F=0.47; p=0.628), 10.6% (R2=0.106; F=3.03; p=0.057), and 10.1% (R2=0.101; F=2.70; p=0.077) of the variability, respectively. None of the regression models developed for the abdominal muscles exhibited statistical significance. A significant and negative association (p=0.018; β=-0.0343) was observed only between UI and IO recruitment. Conclusion: These results suggest that age-related factors may have interfered with the findings of the study, thus emphasizing the need to perform ultrasound imaging-based studies to measure abdominal muscle recruitment in the elderly.

CONTEXTUALIZAÇÃO: Pessoas com dor lombar com altos níveis de lócus de controle externo têm piores prognósticos e necessitam de melhores intervenções ativas, uma vez que elas são consideradas mais valiosas. Se os níveis de lócus de controle diferem entre os participantes com dor lombar e aqueles que esperam o tratamento, a relação do atendimento-paciente não está clara. OBJETIVO: Investigar se existem diferenças no lócus de controle entre os indivíduos com dor lombar crônica em tratamento (grupo tratamento) e aqueles que esperam tratamento (grupo controle). MÉTODOS: Cem participantes (50 por grupo) com sintomas lombares por pelo menos três meses, com um episódio atual de dor lombar e com idades entre 18 e 60 anos foram recrutados. O Questionário Multidimensional de Lócus de Controle da Saúde (MHLC) foi usado para coleta das crenças dos participantes. Realizou-se uma regressão linear múltipla ajustada para incapacidade e para comparação do lócus de controle entre os grupos. As diferenças foram descritas com médias e intervalos de confiança de 95%. RESULTADOS: O grupo tratamento teve escore mais alto para o lócus de controle externo e mais baixo para o lócus de controle interno quando comparado com o grupo controle. As diferenças médias (intervalo de confiança de 95%) foram 2,7 pontos em possível diferença de até 30 pontos (0,5 a 4,8) para lócus de controle externo e -2,8 pontos (-5,4 a -0,1) para lócus de controle interno. CONCLUSÃO: O lócus de controle da saúde encontrado para o grupo tratamento e o controle foi diferente. Os participantes em tratamento tinham um alto lócus de controle externo e um baixo lócus de controle interno quando comparados com os do grupo controle.

BACKGROUND: People with low back pain (LBP) with higher levels of external locus of control have a poorer prognosis and require greater improvements from active interventions in order to consider these interventions worthwhile. Whether locus of control levels differ between participants with LBP in a patient-health provider relationship and those waiting for treatment is unclear. OBJECTIVE: The aim was to investigate if differences in locus of control exist between participants with non-specific chronic LBP being treated (treatment group) and those waiting treatment (control group). METHODS: 100 participants (50 per group) with low back symptoms for at least three months for the current episode of LBP and aged between 18 and 60 years were recruited. Multidimensional health locus of control questionnaire (MHLC) was used to collect their beliefs. Multiple linear regression adjusted for disability was used to compare health locus of control between both groups. Differences were described as mean differences and 95% confidence intervals. RESULTS: Treatment group scored higher for external locus of control and lower for internal locus of control than control group. Mean differences (95% confidence intervals) were 2.7 points on possible 30-points difference (0.5 to 4.8) for external locus of control and -2.8 points (-5.4 to -0.1) for internal subscale. CONCLUSION: Health locus of control was found to be different between treatment and control groups. Participants being treated had higher external locus of control and lower internal locus of control than control group.