Who is leading the campaign charts? Comparing individual popularity on old and new media

Attention in the mass media is seen as crucial for electoral success. However, most ordinary candidates hardly get any attention in the news. With social media outlets becoming ever more popular, the question is whether the overall asymmetry in attention for candidates still holds today. Do candidates who dominate the traditional media during the campaign also dominate the social media? Or can candidates make up for a lack of mass media coverage by attracting attention on these new media platforms? This paper aims to answer these questions by pairing Twitter activity and Twitter popularity with newspaper attention for a large number of individual candidates in the 2014 Belgian election campaign. We expand the normalization versus equalization debate by not only looking at how much a new medium is used, but also at its success in terms of popularity and audience reach. Our findings show that the two platforms are indeed related, mainly because a small political elite dominates both old and new media. Twitter popularity and Twitter activity (albeit to a lesser extent) are higher among powerful politicians. We elaborate on why these findings are so much in line with the normalization hypothesis.     

Personality profiles of factitious disorder imposed by mothers: A comparative analysis

Factitious Disorder Imposed by Another (FDIA) can be difficult to expeditiously identify. Understanding personality characteristics of FDIA perpetrators via psychological assessment may decrease the time between initial abuse and identification of FDIA. Personality characteristics of FDIA mother-perpetrators were examined through a comparative analysis of MMPI-2 profiles. It was predicted that mother-perpetrators would have significantly higher overall profile elevations on the MMPI-2 and elevations on specific clinical scales than a comparative control group. Results indicated that mother-perpetrators displayed significantly higher, elevations on the Psychasthenia (Pt) and Schizophrenia (Sc) scales and a trend toward significantly higher elevation on the Psychopathic Deviate (Pd) scale than the control group. These findings, along with the demographic information obtained, establish a preliminary foundation for understanding an overall profile of mother-perpetrators.     

Sexuality in Older Adults (65+)—An Overview of the Literature,Part 1: Sexual Function and its Difficulties

Objectives: The aim of the current article was to provide an overview of literature on sexual function and sexual difficulties in older adults. Method: The authors conducted a narrative review of papers published in English between January 2005 and July 2015 based on an extensive search in PsycINFO. Results: The review showed that although common biological changes may adversely affect sexual function in old age, sexual experience seems to also be affected by psychological and interpersonal factors. Conclusions: Greater life expectancy and better medical care will result in older individuals with chronic diseases living longer. The need for help to cope with changes in sexual health is likely to increase in older adults, as sexuality may be negatively affected through several pathways.     

Approximate confidence intervals for the weighted kappa coefficient of a binary diagnostic test subject to a case–control design

Case–control design to assess the accuracy of a binary diagnostic test (BDT) is very frequent in clinical practice. This design consists of applying the diagnostic test to all of the individuals in a sample of those who have the disease and in another sample of those who do not have the disease. The sensitivity of the diagnostic test is estimated from the case sample and the specificity is estimated from the control sample. Another parameter which is used to assess the performance of a BDT is the weighted kappa coefficient. The weighted kappa coefficient depends on the sensitivity and specificity of the diagnostic test, on the disease prevalence and on the weighting index. In this article, confidence intervals are studied for the weighted kappa coefficient subject to a case–control design and a method is proposed to calculate the sample sizes to estimate this parameter. The results obtained were applied to a real example.     

Monitoring the parameter vector of regression models with time-to-event response in phase II processes

In most of the existing specialized literature, monitoring regression models are a special case of profile monitoring. However, not every regression model always represents appropriately a profile data structure. This is clearly the case of the Weibull regression model (WRM) with common shape parameter γ. Even though it might be thought that existing methodologies (especially likelihood-ratio (LRT)-based methods) for monitoring generalized linear profiles can also be successfully applied to monitoring regression models with time-to-event response, it will be shown in this paper that those methodologies work fairly acceptable just for data structures with 1000 observations at least approximately. It was found out that some corrections, often referred to as Bartlett's adjustments, are needed to be implemented in order to improve the accuracy of using the asymptotic distributional properties of the LRT statistic for carrying out the monitoring of WRM with relatively small and moderate dimensions of the available datasets. Simulation studies suggest that the use of the aforementioned corrections make the resulting charts work quite acceptable when available data structures contain 30 observations at least. Detection abilities of the proposed schemes improve as dataset dimension increases.     

A note on the Cauchy-type mixture distributions

An interesting class of continuous distributions, called Cauchy-type mixture, with potential applications in modelling erratic phenomena is introduced by Soltani and Tafakori [A class of continuous kernels and Cauchy type heavy tail distributions. Statist Probab Lett. 2013;83:1018–1027]. In this work, we provide more insights into the Cauchy-type mixture distributions, involving certain characterizations, connections with the generalized Linnik distributions and the class of discrete distributions induced by stable laws. We also prove that the Laplace transform of Cauchy-type mixture distributions when normalized by constant terms become as a density functions in terms of distributional conjugate property.     

A closer look at de-aliasing effects using an efficient foldover technique

Foldover techniques are used to reduce the confounding when some important effects (usually lower order effects) cannot be estimated independently. This article develops an efficient foldover mechanism for symmetric or asymmetric designs, whether regular or nonregular. In this paper, we take the uniformity criteria (UC) as the optimality measures to construct the optimal combined designs (initial design plus its corresponding foldover design) which have better capability of estimating lower order effects. The relationship between any initial design and its combined design is studied. A comparison study between the combined designs via different UC is provided. Equivalence between any combined design and its complementary combined design is investigated, which is a very useful constraint that reduce the search space. Using our results as benchmarks, we can implement a powerful algorithm for constructing optimal combined designs. Our work covers as well as gives results better than recent works of about 20 articles in the last few years as special cases. So this article is a good reference for constructing effective designs.     

Estimation and diagnostic for skew-normal partially linear models

Partially linear models (PLMs) are an important tool in modelling economic and biometric data and are considered as a flexible generalization of the linear model by including a nonparametric component of some covariate into the linear predictor. Usually, the error component is assumed to follow a normal distribution. However, the theory and application (through simulation or experimentation) often generate a great amount of data sets that are skewed. The objective of this paper is to extend the PLMs allowing the errors to follow a skew-normal distribution [A. Azzalini, A class of distributions which includes the normal ones, Scand. J. Statist. 12 (1985), pp. 171–178], increasing the flexibility of the model. In particular, we develop the expectation-maximization (EM) algorithm for linear regression models and diagnostic analysis via local influence as well as generalized leverage, following [H. Zhu and S. Lee, Local influence for incomplete-data models, J. R. Stat. Soc. Ser. B 63 (2001), pp. 111–126]. A simulation study is also conducted to evaluate the efficiency of the EM algorithm. Finally, a suitable transformation is applied in a data set on ragweed pollen concentration in order to fit PLMs under asymmetric distributions. An illustrative comparison is performed between normal and skew-normal errors.     

Optimal design of the adaptive exponentially weighted moving average control chart over a range of mean shifts

The adaptive exponentially weighted moving average (AEWMA) control chart is a smooth combination of the Shewhart and exponentially weighted moving average (EWMA) control charts. This chart was proposed by Cappizzi and Masarotto (2003) to achieve a reasonable performance for both small and large shifts. Cappizzi and Masarotto (2003) used a pair of shifts in designing their control chart. In this study, however, the process mean shift is considered as a random variable with a certain probability distribution and the AEWMA control chart is optimized for a wide range of mean shifts according to that probability distribution and not just for a pair of shifts. Using the Markov chain technique, the results show that the new optimization design can improve the performance of the AEWMA control chart from an overall point of view relative to the various designs presented by Cappizzi and Masarotto (2003). Optimal design parameters that achieve the desired in-control average run length (ARL) are computed in several cases and formulas used to find approximately their values are given. Using these formulas, the practitioner can compute the optimal design parameters corresponding to any desired in-control ARL without the need to apply the optimization procedure. The results obtained by these formulas are very promising and would particularly facilitate the design of the AEWMA control chart for any in-control ARL value.