Statement of Withdrawal: Statistical analysis of an endemic disease from a capture–recapture experiment

There are a number of statistical techniques for analysing epidemic outbreaks. However, many diseases are endemic within populations and the analysis of such diseases are complicated by changing population demography. Motivated by the spread of cowpox among rodent populations, a combined mathematical model for population and disease dynamics is introduced. An MCMC algorithm is then constructed to make statistical inference for the model based on data being obtained from a capture–recapture experiment. The statistical analysis is used to identify the key elements in the spread of the cowpox virus.     

Nonparametric Shrinkage Estimation for Aalen's Additive Hazards Model

Aalen's nonparametric additive model in which the regression coefficients are assumed to be unspecified functions of time is a flexible alternative to Cox's proportional hazards model when the proportionality assumption is in doubt. In this paper, we incorporate a general linear hypothesis into the estimation of the time‐varying regression coefficients. We combine unrestricted least squares estimators and estimators that are restricted by the linear hypothesis and produce James‐Stein‐type shrinkage estimators of the regression coefficients. We develop the asymptotic joint distribution of such restricted and unrestricted estimators and use this to study the relative performance of the proposed estimators via their integrated asymptotic distributional risks. We conduct Monte Carlo simulations to examine the relative performance of the estimators in terms of their integrated mean square errors. We also compare the performance of the proposed estimators with a recently devised LASSO estimator as well as with ridge‐type estimators both via simulations and data on the survival of primary billiary cirhosis patients.     

Digit ratios (2D:4D) as predictors of risky decision making for both sexes

Many important decisions involve financial risk, and substantial evidence suggests that women tend to be more risk averse than men. We explore a potential biological basis of risk-taking variation within and between the sexes by studying how the ratio between the length of the second and fourth fingers (2D:4D) predicts risk-taking. A smaller 2D:4D ratio has been linked to higher exposure to prenatal testosterone relative to estradiol, with men having lower ratios than women. In financially motivated decision-making tasks, we find that men and women with smaller 2D:4D ratios chose significantly riskier options. We further find that the ratio partially explains the variation in risk-taking between the sexes. Moreover, for men and women at the extremes of the digit-ratio distribution the difference in risk-taking disappears. Thus, the 2D:4D ratio partially explains variation in financial risk-taking behavior within and between sexes and offers evidence of a biological basis for risk-taking behavior.     

The Distribution of Returns to Education for People with Disabilities

This article takes a first look at the distribution of returns to education for people with disabilities, a particularly disadvantaged group whose labor market performances have not been well studied or documented. Using a nonparametric approach, we uncover significant heterogeneity in the returns to education for these workers, which is drastically masked by conventional parametric methods. Based on these estimates, we construct the Sharpe ratio of human capital investment (taking into account its substantial risk), and our results corroborate the claimed importance of human capital in improving these workers’ wages. Our stochastic dominance tests show that the returns to education for workers with disabilities, as a group, may have been affected more adversely in the most recent recession, relative to their non-disabled counterparts.     

“Service” Municipal Administration as Part of the Development of Youth Entrepreneurship in Russia

The study offers a development of the social technologies of “service” municipal administration. The consumers’ opinions should be taken into consideration when determining the nomenclature and standards of their provision, which include the quality parameters that the consumers consider important. In addition, “service” relations imply the assessment of consumer satisfaction with the services and the correction of services based on the results of the assessment. Since this interaction implies communication between the municipal administration body and service users, it is necessary to focus on communicative technologies that are capable of providing a full cycle of service development and improvement for young entrepreneurs. Communications should help determine the expectations associated with a service, raise awareness thereof, and involve young people in the decisions related to the provision of services.     

Are sponsors blamed for edging off? Consumer reactions to sponsorship terminations

Firms regularly terminate sponsorships, even without publicly known misconduct by the sponsee such as athlete doping. Consumer reactions to these sponsorship terminations by firms have not been studied despite being a regular occurrence. Using a set of experimental studies, this paper analyzes consumer reactions to these sponsorship terminations (i.e., early and non-renewal) that were not caused by a sponsee’s misconduct, the underlying process that causes the reactions, and the role of several moderating factors (trust, power balance, and locus of control). Our findings reveal that sponsorship terminations have a negative effect on sponsors’ brand images—particularly early terminations that occur before the end of a contract—because consumers perceive these sponsorship terminations as unfair. The results also suggest that a termination is particularly harmful for the sponsor’s perceived fairness if the sponsor is powerful and if the termination decision is under the sponsor’s control. Further, the termination effect is particularly strong for firms that consumers trust.     

Penalized empirical likelihood inference for sparse additive hazards regression with a diverging number of covariates

High-dimensional sparse modeling with censored survival data is of great practical importance, as exemplified by applications in high-throughput genomic data analysis. In this paper, we propose a class of regularization methods, integrating both the penalized empirical likelihood and pseudoscore approaches, for variable selection and estimation in sparse and high-dimensional additive hazards regression models. When the number of covariates grows with the sample size, we establish asymptotic properties of the resulting estimator and the oracle property of the proposed method. It is shown that the proposed estimator is more efficient than that obtained from the non-concave penalized likelihood approach in the literature. Based on a penalized empirical likelihood ratio statistic, we further develop a nonparametric likelihood approach for testing the linear hypothesis of regression coefficients and constructing confidence regions consequently. Simulation studies are carried out to evaluate the performance of the proposed methodology and also two real data sets are analyzed.     

Volunteer Engagement: Exploring the Distinction Between Job and Organizational Engagement

Retaining engaged volunteers is crucial to many non-profit organizations. However, research on volunteer engagement is limited, and the distinction between job and organizational engagement in volunteers remains to be investigated. In this paper, we examine both organizational- and job-level engagement, and specifically, whether perceived organizational support would enhance volunteer engagement and associated attitudes. We surveyed 221 volunteers, and asked them about their perceptions of organizational support; their engagement with their volunteer job and the organization they volunteer for; satisfaction; commitment; and turnover intentions. Both organizational and job engagements had significant relationships with the attitudinal variables. However, we found that organizational rather than job engagement mediated the relationship between organizational support and volunteer satisfaction and commitment. While organizational engagement correlated with turnover intentions, neither job nor organizational engagement mediated the relationship between support and the intent to leave. Our findings advance the research on volunteer engagement, and highlight the importance of organizational engagement for this important, but too often overlooked, workforce.