Shared frailty model for recurrent event data with multiple causes

The topic of heterogeneity in the analysis of recurrent event data has received considerable attention recent times. Frailty models are widely employed in such situations as they allow us to model the heterogeneity through common random effect. In this paper, we introduce a shared frailty model for gap time distributions of recurrent events with multiple causes. The parameters of the model are estimated using EM algorithm. An extensive simulation study is used to assess the performance of the method. Finally, we apply the proposed model to a real-life data.     

Bivariate symmetry tests for complete and competing risks data: a saddlepoint approach

A class of bivariate symmetry tests for complete data and competing risks data is considered. Saddlepoint approximation for the exact p-values of the underlying permutation distribution of these tests is derived. Several simulation studies are conducted to evaluate the performance of the saddlepoint approximation and the asymptotic approximation. The saddlepoint approximation was found to be highly accurate and superior to the asymptotic approximations in replicating the exact permutation significance.     

Decision-making in Social Work Field Education: A “Good Enough” Framework

This qualitative study was designed to explore decision-making processes used by directors of field education in social work programs in the USA. It is a follow-up to previous research showing the dilemmas that field directors face [specifics deleted to maintain the integrity of the review process]. We asked 22 field directors to explain how they would handle different dilemmas designed to simulate the kinds of issues that typically arise in field education. Analyses revealed that field directors use a four-dimensional decision-making process to address competing demands, employing a ‘good enough’ framework. The four dimensions include student learning, professional ethics, agency relationships, and administrative expectations.     

现代汉语NV式状中偏正结构浅探

名词直接修饰动词、名词做状语、动词做中心语的NV式状中偏正结构中名词与动词之间的语义关系有三种：(1)N表示V的方式、手段；(2)N表示V的情态；(3)N表示V的程度。动因竞争是NV式状中偏正结构形成的原因。在这个结构中名词是受到限制的，只有不能做施事的名词才能与动词构成NV式状中偏正结构。     

Statistical methods for dependent competing risks

Many biological and medical studies have as a response of interest the time to occurrence of some event,X, such as the occurrence of cessation of smoking, conception, a particular symptom or disease, remission, relapse, death due to some specific disease, or simply death. Often it is impossible to measureX due to the occurrence of some other competing event, usually termed a competing risk. This competing event may be the withdrawal of the subject from the study (for whatever reason), death from some cause other than the one of interest, or any eventuality that precludes the main event of interest from occurring. Usually the assumption is made that all such censoring times and lifetimes are independent. In this case one uses either the Kaplan-Meier estimator or the Nelson-Aalen estimator to estimate the survival function. However, if the competing risk or censoring times are not independent ofX, then there is no generally acceptable way to estimate the survival function. There has been considerable work devoted to this problem of dependent competing risks scattered throughout the statistical literature in the past several years and this paper presents a survey of such work.     

Management Errors and System Reliability: A Probabilistic Approach and Application to Offshore Platforms

Probabilistic risk analysis, based on the identification of failure modes, points to technical malfunctions and operator errors that can be direct causes of system failure. Yet component failures and operator errors are often rooted in management decisions and organizational factors. Extending the analysis to identify these factors allows more effective risk management strategies. It also permits a more realistic assessment of the overall failure probability. An implicit assumption that is often made in PRA is that, on the whole, the system has been designed according to specified norms and constructed as designed. Such an analysis tends to overemphasize scenarios in which the system fails because it is subjected to a much higher load than those for which it was designed. In this article, we find that, for the case of jacket-type offshore platforms, this class of scenarios contributes only about 5% of the failure probability. We link the PRA inputs to decisions and errors during the three phases of design, construction, and operation of platforms, and we assess the contribution of different types of error scenarios to the overall probability of platform failure. We compute the benefits of improving the design review, and we find that, given the costs involved, improving the review process is a more efficient way to increase system safety than reinforcing the structure.     

Women in the American Political System

No abstract available for this article.     

Confidence bounds for the joint survival function in the dependent competing risks setup

In the competing risks set up with two dependent competing risks, the joint distribution of (X₁,X₂), the latent lifetimes of the system under the two risks, is not identifiable on the basis of the distribution of the actual observation (T, δ) where T = min(X₁, X₂) and δ = I(T=X₁), Using Peterson's (1976) bounds, we have obtained conservative pointwise as well as simultaneous confidence bounds for the unidentifiable joint survival function. In an example we evaluate the confidence bounds and Indicate where the estimated joint survival function in the independent case, lies within them.     

The analysis of transition times in multistate stochastic processes using proportional hazard regression models

Extensions to Cox's proportional hazards regression model (Cox, 1972) for the analysis of survival data are considered for a more general multistate framework. This framework allows several transient disease states between initial entry state and death as well as incorporating possible competing causes of death. Methods for parameter and function estimation within this extension are presented and applied to the analysis of data from the Stanford Heart Transplantation Program (Crowley and Hu,1977).     

The random partition masking model for interval-censored and masked competing risks data

We study the nonparametric maximum likelihood estimate (NPMLE) of the cdf or sub-distribution functions of the failure time for the failure causes in a series system. The study is motivated by a cancer research data (from the Memorial Sloan-Kettering Cancer Center) with interval-censored time and masked failure cause. The NPMLE based on this data set suggests that the existing masking models are not appropriate. We propose a new model called the random partition masking model, which does not rely on the commonly used symmetry assumption (namely, given the failure cause, the probability of observing the masked failure causes is independent of the failure time; see Flehinger et al. Inference about defects in the presence of masking, Technometrics 38 (1996), pp. 247–255). The RPM model is easier to implement in simulation studies than the existing models. We discuss the algorithms for computing the NPMLE and study its asymptotic properties. Our simulation and data analysis indicate that the NPMLE is feasible for a moderate sample size.