How Are Money Worries Affecting Middle-Aged,Young-Old,and Old–Old People’s Perceived Couple Relationship?

While the association between financial strain and couple interaction has been well-established in the literature on economic stress, little research has investigated the association among middle-aged and older populations. The present study examined the relationships between financial strain and couple functioning of middle-aged, young-old, and old–old people using the 2010 Health and Retirement Study. Findings show that subjective financial strain was positively associated with partner undermining and negatively with partner support, controlling for the effects of objective financial situations among middle-aged, young-old, and old–old couples. There were gender and age differences in the interaction effects of financial strain and financial control on couple functioning. For middle-aged men, financial control may have different associations with couple behaviors depending on the level of financial strain. When the level of financial strain is high, the positive effect of financial control disappears and the effect changes even in a negative way. Findings provide suggestions for practitioners and researchers.     

Interpersonal and Societal Mattering in Work: A Review and Critique

The need exists for a comprehensive literature review of the concept of mattering with regard to work. In response, this review examined a theoretical framework of societal and interpersonal mattering, mattering within the work context, and existing psychometric measures of mattering. The author analyzed the research on the current state of mattering at work, identified core frameworks and psychometric issues that have been investigated to date, and suggests the use of a more comprehensive framework for work mattering that illuminates both the relational and social aspects of the work experience. Several promising directions for future research and potential benefits of incorporating work mattering in career counseling practice emerged and are discussed.     

Utilizing Bayesian predictive power in clinical trial design

The Bayesian paradigm provides an ideal platform to update uncertainties and carry them over into the future in the presence of data. Bayesian predictive power (BPP) reflects our belief in the eventual success of a clinical trial to meet its goals. In this paper we derive mathematical expressions for the most common types of outcomes, to make the BPP accessible to practitioners, facilitate fast computations in adaptive trial design simulations that use interim futility monitoring, and propose an organized BPP-based phase II-to-phase III design framework.     

Acculturative Stress and Mental Health Among Korean Adolescents in the United States

This study investigated Korean-American adolescents' stress related to their acculturation experiences and mental health. A total of 260 Korean-American adolescents from immigrant families (ages 12–18 years) participated in the study. The U.S. born group had a higher level of acculturative stress than the Korea-born group (t = 2.222; df = 258; p < .05). Males reported a higher level of self-esteem than females (t = ?2.112; df = 257; p < .05). Acculturative stress was positively correlated with depression (r = .299; p < .01) and negatively related to self-esteem (r = ?.292; p < .01). Self-esteem was negatively related to depression (r = ?.536; p < .01).     

Designs for estimating the difference between two responses

In this paper the problem of designing experiments for estimating the difference between responses at two arbitrary points in the region of interest is considered. Under the average mean squared error criterion the design moment conditions have been worked out. The results have been applied to the class of central composite designs.     

The estimation of treatment effect for the censored bivariate data under the univariate censoring

This paper establishes a nonparametric estimator for the treatment effect on censored bivariate data under unvariate censoring. This proposed estimator is based on the one from Lin and Ying(1993)'s nonparametric bivariate survival function estimator, which is itself a generalized version of Park and Park(1995)' quantile estimator. A Bahadur type representation of quantile functions were obtained from the marginal survival distribution estimator of Lin and Ying' model. The asymptotic property of this estimator is shown below and the simulation studies are also given     

Linear filter model representations for integrated process control with repeated adjustments and monitoring

An integrated process control (IPC) procedure is a scheme which combines the engineering process control (EPC) and the statistical process control (SPC) procedures for the process where the noise and a special cause are present. The most efficient way of reducing the effect of the noise is to adjust the process by its forecast, which is done by the EPC procedure. The special cause, which produces significant deviations of the process level from the target, can be detected by the monitoring scheme, which is done by the SPC procedure. The effects of special causes can be eliminated by a rectifying action. The performance of the IPC procedure is evaluated in terms of the average run length (ARL) or the expected cost per unit time (ECU). In designing the IPC procedure for practical use, it is essential to derive its properties constituting the ARL or ECU based on the proposed process model. The process is usually assumed as it starts only with noise, and special causes occur at random times afterwards. The special cause is assumed to change the mean as well as all the parameters of the in-control model. The linear filter models for the process level as well as the controller and the observed deviations for the IPC procedure are developed here.     

Semiparametric transformation models for multivariate panel count data with dependent observation process

This article discusses regression analysis of multivariate panel count data in which the observation process may contain relevant information about or be related to the underlying recurrent event processes of interest. Such data occur if a recurrent event study involves several related types of recurrent events and the observation scheme or process may be subject-specific. For the problem, a class of semiparametric transformation models is presented, which provides a great flexibility for modelling the effects of covariates on the recurrent event processes. For estimation of regression parameters, an estimating equation-based inference procedure is developed and the asymptotic properties of the resulting estimates are established. Also the proposed approach is evaluated by simulation studies and applied to the data arising from a skin cancer chemoprevention trial.