Reducing sample size needed for cox-proportional hazards model analysis using more efficient sampling method

Abstract

In general, survival data are time-to-event data, such as time to death, time to appearance of a tumor, or time to recurrence of a disease. Models for survival data have frequently been based on the proportional hazards model, proposed by Cox. The Cox model has intensive application in the field of social, medical, behavioral and public health sciences. In this paper we propose a more efficient sampling method of recruiting subjects for survival analysis. We propose using a Moving Extreme Ranked Set Sampling (MERSS) scheme with ranking based on an easy-to-evaluate baseline auxiliary variable known to be associated with survival time. This paper demonstrates that this approach provides a more powerful testing procedure as well as a more efficient estimate of hazard ratio than that based on simple random sampling (SRS). Theoretical derivation and simulation studies are provided. The Iowa 65+ Rural study data are used to illustrate the methods developed in this paper.     

我国国民教育投资现状与对策研究

本文阐述了我国教育投资的现状及存在的问题,分析了我国教育投资不足的原因及制定教育投资政策的理论依据,并进一步提出建设适合我国国情的教育投资制度的思路和对策。     

Fitting competing risks data to bivariate Pareto models

This paper revisits two bivariate Pareto models for fitting competing risks data. The first model is the Frank copula model, and the second one is a bivariate Pareto model introduced by Sankaran and Nair (1993 Sankaran, P. G., and N. U. Nair. 1993. A bivariate Pareto model and its applications to reliability. Naval Research Logistics 40 (7):1013–1020. doi:10.1002/1520-6750(199312)40:7%3c1013::AID-NAV3220400711%3e3.0.CO;2-7.[Crossref], [Web of Science ®] , [Google Scholar]). We discuss the identifiability issues of these models and develop the maximum likelihood estimation procedures including their computational algorithms and model-diagnostic procedures. Simulations are conducted to examine the performance of the maximum likelihood estimation. Real data are analyzed for illustration.     

论新媒体冲击下纸媒的生存与发展——以报纸为例

互联网的发展、智能手机的普及使传统的传媒环境和格局发生了翻天覆地的变化。新媒体的崛起与壮大给以纸媒为代表的传统媒体带来了前所未有的冲击，但不可否认的是，纸媒自身依然有不可替代的优势。本文主要以报纸为例，从纸媒传播内容的深度和可信度、纸媒对于受众文化素质的要求以及纸媒的表现形式、和受众的互动等方面的特点入手，分析在新媒体的冲击下纸媒所面临的生存现状，并且在此基础上指出将来纸媒应该如何利用新媒体的技术来促进自身的发展，更好地实现新媒体与传统媒体的融合。     

戴维森意义理论的主要思想导源

戴维森意义理论具有明显的思想继承性,主要表现在:弗雷格的真值条件论是其基本立足点,塔尔斯基真之语义论的约定-T模式充当其形式表征基础,蒯因的彻底翻译理论成为其经验解释的理论基础。正是由于戴维森善于借鉴这些影响深远的思想成果,使其意义理论呈现出一种解释性的真理论而潜在地具有非凡的理论优势和影响力。     

A goodness of fit test for multilevel survival data

No satisfactory goodness of fit test is available for multilevel survival data which occur when survival data are clustered or hierarchical in nature. Hence the aim of this research is to develop a new goodness of fit test for multilevel survival data and to examine the properties of the newly developed test. Simulation studies were carried out to evaluate the type ? error and the power. The results showed that the type I error holds for every combination tested and that the test is powerful against the alternative hypothesis of nonproportional hazards for all combinations tested.     

综述和讨论:关于小民族的生存及前景

作为人类社会、人类文化重要组成部分的小民族的生存及未来前景问题,他们因传统文化特点、因外部社会因素而引发的带有小民族特有特点的现实生存难题,早已引起人类学以及相关学科的高度重视,我国近些年对国内小民族的研究也渐成气象。那么,国内就小民族生存、发展问题的关注和实证研究状况如何?近数十年来,整个学界围绕小民族生存和未来前景以及影响因素的探讨,主要关注了哪些层面?提出了哪些主要观点?从问题意识出发,并结合自己有限的田野工作经验,本文尝试进行初步的综述和讨论。     

Semiparametric Estimation of a Change-point for Recurrent Events Data

One particular recurrent events data scenario involves patients experiencing events according to a common intensity rate, and then a treatment may be applied. The treatment might be effective for a limited amount of time, so that the intensity rate would be expected to change abruptly when the effect of the treatment wears out. In particular, we allow models for the intensity rate, post-treatment, to be at first decreasing and then change to increasing (and vice versa). Two estimators of the location of this change are proposed.     

Estimating the effectiveness of a misdemeanor drug diversion program using propensity score matching and survival analyses

This study analyzes three years of data on misdemeanor drug offenders in Winnebago County, Wisconsin. A portion of these offenders opted into a Misdemeanor Drug Diversion Program (MDDP) offered instead of traditional adjudication. Recidivism in the treatment and comparison groups is estimated using standard binary response techniques augmented with propensity score matching to address selection bias. Results show that the MDDP reduces the probability of re-offense by 16%, after adjusting for possible selection bias. Cox proportional hazard modeling is also used to assess time-to-re-offense differentials between the treatment and comparison groups. The survival analysis indicates that the hazard rate of re-offense is 60% lower per day among those treated with the MDDP program than those who did not complete the program. The average number of days to re-offense among those that do re-offend is 297 days in the treatment group and 203 days in the comparison group.     

The inverse power Lindley distribution

Several probability distributions have been proposed in the literature, especially with the aim of obtaining models that are more flexible relative to the behaviors of the density and hazard rate functions. Recently, two generalizations of the Lindley distribution were proposed in the literature: the power Lindley distribution and the inverse Lindley distribution. In this article, a distribution is obtained from these two generalizations and named as inverse power Lindley distribution. Some properties of this distribution and study of the behavior of maximum likelihood estimators are presented and discussed. It is also applied considering two real datasets and compared with the fits obtained for already-known distributions. When applied, the inverse power Lindley distribution was found to be a good alternative for modeling survival data.