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.     

The Representation of Hypergeometric Random Variables using Independent Bernoulli Random Variables

In this paper, we show that a hypergeometric random variable can be represented as a sum of independent Bernoulli random variables that are, except in degenerate cases, not identically distributed. In the proof, we use the factorial moment generating function. An asymptotic result on the probabilities of the Bernoulli random variables in the sum is also presented. Numerical examples are used to illustrate the results.     

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.     

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).     

Coffee intake,health-related quality of life,and associated factors of overactive bladder in older Korean women living in rural South Korea

ABSTRACT

Overactive bladder (OAB) is a common health problem in older women. The aim of the study was to investigate coffee consumption, health-related quality of life (HRQOL), and associated factors of OAB in older Korean women living in rural South Korea. A total of 248 women aged 65 years and older participated in this study. Chi-square tests, t-tests, and multivariable logistic regressions were performed. The means of coffee consumption between OAB and non-OAB groups were not significantly different. Women with OAB showed significantly lower HRQOL than women with stress urinary incontinence only. OAB was associated with high body mass index and poor health status.     

Testing non-nested log-linear models with pseudo estimator

As the number of random variables for the categorical data increases, the possible number of log-linear models which can be fitted to the data increases rapidly, so that various model selection methods are developed. However, we often found that some models chosen by different selection criteria do not coincide. In this paper, we propose a comparison method to test the final models which are non-nested. The statistic of Cox (1961, 1962) is applied to log-linear models for testing non-nested models, and the Kullback-Leibler measure of closeness (Pesaran 1987) is explored. In log-linear models, pseudo estimators for the expectation and the variance of Cox's statistic are not only derived but also shown to be consistent estimators.     

Bayesian principal component analysis with mixture priors

A central issue in principal component analysis (PCA) is that of choosing the appropriate number of principal components to be retained. Bishop (1999a) suggested a Bayesian approach for PCA for determining the effective dimensionality automatically on the basis of the probabilistic latent variable model. This paper extends this approach by using mixture priors, in that the choice dimensionality and estimation of principal components are done simultaneously via MCMC algorithm. Also, the proposed method provides a probabilistic measure of uncertainty on PCA, yielding posterior probabilities of all possible cases of principal components.     

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.     

Inside the blogosphere: A taxonomy and framing analysis of abortion weblogs

This study analyses weblog abortion-related content sampled via a search and snowball method. When weblogs located inside of established media Web sites and other weblogs are compared, they are equivalent in the use of advocacy versus objectivist frames. Media weblog posts contain a political frame more frequently than non-media weblog posts do. In terms of diversity of frame, media weblogs employ more frames in their stories. Various explanations for these findings are offered in the context of current abortion-related content patterns.