Multiple event times in the presence of informative censoring: modeling and analysis by copulas

Motivated by a breast cancer research program, this paper is concerned with the joint survivor function of multiple event times when their observations are subject to informative censoring caused by a terminating event. We formulate the correlation of the multiple event times together with the time to the terminating event by an Archimedean copula to account for the informative censoring. Adapting the widely used two-stage procedure under a copula model, we propose an easy-to-implement pseudo-likelihood based procedure for estimating the model parameters. The approach yields a new estimator for the marginal distribution of a single event time with semicompeting-risks data. We conduct both asymptotics and simulation studies to examine the proposed approach in consistency, efficiency, and robustness. Data from the breast cancer program are employed to illustrate this research.

     

Doing Good and Selling Goods

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - This paper explores a network of organizations and their perspectives on the social enterprise commodity. Based on...     

A new long-term survival model with dispersion induced by discrete frailty

Lifetime Data Analysis - Frailty models are generally used to model heterogeneity between the individuals. The distribution of the frailty variable is often assumed to be continuous. However, there...     

Partial Identification of Economic Mobility: With an Application to the United States

Abstract

The economic mobility of individuals and households is of fundamental interest. While many measures of economic mobility exist, reliance on transition matrices remains pervasive due to simplicity and ease of interpretation. However, estimation of transition matrices is complicated by the well-acknowledged problem of measurement error in self-reported and even administrative data. Existing methods of addressing measurement error are complex, rely on numerous strong assumptions, and often require data from more than two periods. In this article, we investigate what can be learned about economic mobility as measured via transition matrices while formally accounting for measurement error in a reasonably transparent manner. To do so, we develop a nonparametric partial identification approach to bound transition probabilities under various assumptions on the measurement error and mobility processes. This approach is applied to panel data from the United States to explore short-run mobility before and after the Great Recession.     

Behavioral responses of rural and urban greater white-toothed shrews (Crocidura russula) to sound disturbance

Urban Ecosystems - The development of urban areas imposes challenges that wildlife must adapt to in order to persist in these new habitats. One of the greatest changes brought by urbanization has...     

Inference and Decision Making for 21st-Century Drug Development and Approval

ABSTRACT

The cost and time of pharmaceutical drug development continue to grow at rates that many say are unsustainable. These trends have enormous impact on what treatments get to patients, when they get them and how they are used. The statistical framework for supporting decisions in regulated clinical development of new medicines has followed a traditional path of frequentist methodology. Trials using hypothesis tests of “no treatment effect” are done routinely, and the p-value < 0.05 is often the determinant of what constitutes a “successful” trial. Many drugs fail in clinical development, adding to the cost of new medicines, and some evidence points blame at the deficiencies of the frequentist paradigm. An unknown number effective medicines may have been abandoned because trials were declared “unsuccessful” due to a p-value exceeding 0.05. Recently, the Bayesian paradigm has shown utility in the clinical drug development process for its probability-based inference. We argue for a Bayesian approach that employs data from other trials as a “prior” for Phase 3 trials so that synthesized evidence across trials can be utilized to compute probability statements that are valuable for understanding the magnitude of treatment effect. Such a Bayesian paradigm provides a promising framework for improving statistical inference and regulatory decision making.     

What is educational entrepreneurship? Strategic action,temporality, and the expansion of US higher education

Theory and Society - The massive expansion of US higher education after World War II is a sociological puzzle: a spectacular feat of state capacity-building in a highly federated polity. Prior...     

税务行政裁量权的理论阐释、行为纠偏与路径选择

税法中不确定概念下的理论空间以及税务行政的实践需求共同营造了税务行政裁量的制度空间，而不规范的税务行政裁量则为不规范的税收执法提供了操作机会。通过对税法文本中不确定概念理论缘由的寻求，以及税收征管中实践动因的梳理，税务行政裁量权的规范化确有必要性。为达成税法运行各司其职中的彼此制衡，有必要强化比例性原则在税务行政裁量中的运用，以此限制税权介入纳税人私域的范围与限度，并提供明确化的宏观指引；利用行政裁量基准“行政自制”与“规则之治”的双重品质，借助标准化的文本修正，为规范化的税收执法预设行为轨迹、构建外在制约并压缩裁量空间；以纳税人的同意权为基础，设计符合税法特殊性的程序规则，形成立体化的纳税人救济路径。最终形成税务行政裁量权积极运作与规范运行的制度环境。