A note on bias reduction of maximum likelihood estimates for the scalar skew t distribution

The skew t distribution is a flexible parametric family to fit data, because it includes parameters that let us regulate skewness and kurtosis. A problem with this distribution is that, for moderate sample sizes, the maximum likelihood estimator of the shape parameter is infinite with positive probability. In order to try to solve this problem, Sartori (2006) has proposed using a modified score function as an estimating equation for the shape parameter. In this note we prove that the resulting modified maximum likelihood estimator is always finite, considering the degrees of freedom as known and greater than or equal to 2.     

SOS—Satisfied or Stuck,Why Older Rural Residents Stay Put: Aging in Place or Stuck in Place in Rural Utah*

As rural communities undergo substantial demographic and economic changes, understanding the migration intentions and their antecedents of rural elderly persons becomes increasingly important. Using data drawn from a survey of adults from 24 rural Utah communities conducted in 2008, we examine whether rural residents 60 years of age or older plan to remain in their present communities (N= 621). We use structural equation models (SEM) to estimate the relationships between a variety of individual and community-level background measures, including perceptions of local service quality, leaving one's community for health care, Internet use, attachment to and satisfaction with community, and plans to age in place. Results suggest that even as the rural context of economic decline, population loss, and distance to medical services may reduce the viability of staying in a community, a desire to remain in the community is primarily a function of perceptions of the quality of local services and community satisfaction. This research highlights the need to better understand the interplay between the availability of medical services and perceptions of distance as well as to understand the complex relationship between individual and community level characteristics for migration intentions.     

Time series models based on the unrestricted skew-normal process

The standard location and scale unrestricted (or unified) skew-normal (SUN) family studied by Arellano-Valle and Genton [On fundamental skew distributions. J Multivar Anal. 2005;96:93–116] and Arellano-Valle and Azzalini [On the unification of families of skew-normal distributions. Scand J Stat. 2006;33:561–574], allows the modelling of data which is symmetrically or asymmetrically distributed. The family has a number of advantages suitable for the analysis of stochastic processes such as Auto-Regressive Moving-Average (ARMA) models, including being closed under linear combinations, being able to satisfy the consistency condition of Kolmogorov’s theorem and providing the guarantee of the existence of such a SUN stochastic process. The family is able to be represented in a hierarchical form which can be used for the ease of simulation. In addition, it facilitates an EM-type algorithm to estimate the model parameters. The performances and suitability of the proposed model are demonstrated on simulations and using two real data sets in applications.     

Gambling motivations and superstitious beliefs: a cross-cultural study with casino customers

The expansion of legalized commercial gaming in Macau has motivated stakeholders to explore opportunities in other Asian countries. However, there is a lack of research focusing on casino customers in these markets. Thus, the purpose of this study is to explore gambling superstitious beliefs and motivations of those visiting a casino in South Korea, and how these factors are different across four ethnic groups. The researchers surveyed 323 casino customers in the lounge area on the casino floor, including Americans, Chinese, Japanese, and Koreans living abroad. This study found American gamblers could be characterized as more superstitious than Japanese gamblers, while the Chinese and American gamblers exhibited many similarities regarding the pattern of superstitious beliefs that they were most likely to endorse. The findings also suggest the culture and the area around the casino might be more important to Chinese, while novelty to Japanese and winning money to Korean gamblers are seen as most important. This study contributes to gambling literature by examining gamblers’ beliefs and motives in a different setting with more diverse populations than those in previous studies. The findings of this study will help casino operators properly develop and adjust strategies to thrive in the Asian marketplace.     

What is Sexual Satisfaction? Thematic Analysis of Lay People's Definitions

Sexual satisfaction is an important indicator of sexual health and is strongly associated with relationship satisfaction. However, research exploring lay definitions of sexual satisfaction has been scarce. We present thematic analysis of written responses of 449 women and 311 men to the question “How would you define sexual satisfaction?” The participants were heterosexual individuals with a mean age of 36.05 years (SD = 8.34) involved in a committed exclusive relationship. In this exploratory study, two main themes were identified: personal sexual well-being and dyadic processes. The first theme focuses on the positive aspects of individual sexual experience, such as pleasure, positive feelings, arousal, sexual openness, and orgasm. The second theme emphasizes relational dimensions, such as mutuality, romance, expression of feelings, creativity, acting out desires, and frequency of sexual activity. Our results highlight that mutual pleasure is a crucial component of sexual satisfaction and that sexual satisfaction derives from positive sexual experiences and not from the absence of conflict or dysfunction. The findings support definitions and models of sexual satisfaction that focus on positive sexual outcomes and the use of measures that incorporate items linked to personal and dyadic sexual rewards for both men and women.     

Leadership of highly creative people in highly creative fields: A historiometric study of scientific leaders

In recent years there has been a marked increase in the study of the influence of leadership on creativity, and the effects of this relationship on organizational performance. While a number of explanations have been broached with regard to the positive effects of leadership on creativity, many of these studies propose different, and often contradictory, methods for leaders to achieve these positive effects on creativity within their organizations and work groups. Additionally, little work has been done examining the effects of leadership on highly creative people in fields requiring creativity. The purpose of this study is to examine two existing leadership theories with regard to their viability as models to explain creative performance of eminent scientists. Eminent scientists represent a population of leaders of highly creative individuals in a field that values the production of innovative ideas and products as a marker of performance. Ninety-three excerpts from the biographies of scientists were content coded for leader behaviors and performance criteria. The results of this analysis indicate that a model based on strategic planning and product championing may serve to explain the positive effects of leadership on creativity in a highly creative population.     

Marginal zero-inflated regression models for count data

Data sets with excess zeroes are frequently analyzed in many disciplines. A common framework used to analyze such data is the zero-inflated (ZI) regression model. It mixes a degenerate distribution with point mass at zero with a non-degenerate distribution. The estimates from ZI models quantify the effects of covariates on the means of latent random variables, which are often not the quantities of primary interest. Recently, marginal zero-inflated Poisson (MZIP; Long et al. [A marginalized zero-inflated Poisson regression model with overall exposure effects. Stat. Med. 33 (2014), pp. 5151–5165]) and negative binomial (MZINB; Preisser et al., 2016) models have been introduced that model the mean response directly. These models yield covariate effects that have simple interpretations that are, for many applications, more appealing than those available from ZI regression. This paper outlines a general framework for marginal zero-inflated models where the latent distribution is a member of the exponential dispersion family, focusing on common distributions for count data. In particular, our discussion includes the marginal zero-inflated binomial (MZIB) model, which has not been discussed previously. The details of maximum likelihood estimation via the EM algorithm are presented and the properties of the estimators as well as Wald and likelihood ratio-based inference are examined via simulation. Two examples presented illustrate the advantages of MZIP, MZINB, and MZIB models for practical data analysis.     

Eliciting children’s recall regarding home life and relationships

Abstract

Child interviews form an important component of custody evaluations. Yet, research on children’s responses to questions about home life and relationships is lacking. In the present study, children (N?=?47) aged 6 to 10?years were interviewed about their daily routines and family relationships. Responses to four categories of questions were compared: open and specific questions about routines, and negative and positive aspects of family relationships. Responses were coded for amount of information, informativeness, topic pertinence, and refusals to answer. Results suggested that questions about everyday routines and relationships elicit relevant and informative responses from children. It is suggested that interviewers begin with open-ended questions regarding daily routines to structure family law interviews with children.     

Estimation and diagnostic analysis in skew-generalized-normal regression models

The skew-generalized-normal distribution [Arellano-Valle, RB, Gómez, HW, Quintana, FA. A new class of skew-normal distributions. Comm Statist Theory Methods 2004;33(7):1465–1480] is a class of asymmetric normal distributions, which contains the normal and skew-normal distributions as special cases. The main virtues of this distribution is that it is easy to simulate from and it also supplies a genuine expectation–maximization (EM) algorithm for maximum likelihood estimation. In this paper, we extend the EM algorithm for linear regression models assuming skew-generalized-normal random errors and we develop a diagnostics analyses via local influence and generalized leverage, following Zhu and Lee's approach. This is because Cook's well-known approach would be more complicated to use to obtain measures of local influence. Finally, results obtained for a real data set are reported, illustrating the usefulness of the proposed method.