Attenuation of treatment effect due to measurement variability in assessment of progression-free survival

For normally distributed data analyzed with linear models, it is well known that measurement error on an independent variable leads to attenuation of the effect of the independent variable on the dependent variable. However, for time‐to‐event variables such as progression‐free survival (PFS), the effect of the measurement variability in the underlying measurements defining the event is less well understood. We conducted a simulation study to evaluate the impact of measurement variability in tumor assessment on the treatment effect hazard ratio for PFS and on the median PFS time, for different tumor assessment frequencies. Our results show that scan measurement variability can cause attenuation of the treatment effect (i.e. the hazard ratio is closer to one) and that the extent of attenuation may be increased with more frequent scan assessments. This attenuation leads to inflation of the type II error. Therefore, scan measurement variability should be minimized as far as possible in order to reveal a treatment effect that is closest to the truth. In disease settings where the measurement variability is shown to be large, consideration may be given to inflating the sample size of the study to maintain statistical power. Copyright © 2012 John Wiley & Sons, Ltd.     

Tree-structured prognostic classification for censored survival data: validation of computationally inexpensive model selection criteria

The performance of computationally inexpensive model selection criteria in the context of tree structured prediction is discussed. It is shown through a simulation study that no one model selection criterion exhibits a uniformly superior performance over a wide range of scenarios. Therefore, a two-stage approach for model selection is suggested and shown to perform satisfactorily. A computationally efficient method of tree-growing within the RECursive Partition and AMalgamation (RECPAM) framework is suggested. The computationally efficient algorithm gives identical results as the original RECPAM tree-growing algorithm. An example of medical data analysis for developing prognostic classification is presented.     

Comparing crossing hazard rate functions by joint modelling of survival and longitudinal data

Abstract

It is one of the important issues in survival analysis to compare two hazard rate functions to evaluate treatment effect. It is quite common that the two hazard rate functions cross each other at one or more unknown time points, representing temporal changes of the treatment effect. In certain applications, besides survival data, we also have related longitudinal data available regarding some time-dependent covariates. In such cases, a joint model that accommodates both types of data can allow us to infer the association between the survival and longitudinal data and to assess the treatment effect better. In this paper, we propose a modelling approach for comparing two crossing hazard rate functions by joint modelling survival and longitudinal data. Maximum likelihood estimation is used in estimating the parameters of the proposed joint model using the EM algorithm. Asymptotic properties of the maximum likelihood estimators are studied. To illustrate the virtues of the proposed method, we compare the performance of the proposed method with several existing methods in a simulation study. Our proposed method is also demonstrated using a real dataset obtained from an HIV clinical trial.     

A polar coordinate transformation for estimating bivariate survival functions with randomly censored and truncated data

This paper proposes a new estimator for bivariate distribution functions under random truncation and random censoring. The new method is based on a polar coordinate transformation, which enables us to transform a bivariate survival function to a univariate survival function. A consistent estimator for the transformed univariate function is proposed. Then the univariate estimator is transformed back to a bivariate estimator. The estimator converges weakly to a zero-mean Gaussian process with an easily estimated covariance function. Consistent truncation probability estimate is also provided. Numerical studies show that the distribution estimator and truncation probability estimator perform remarkably well.     

Nonparametric Test for Doubly Interval-Censored Failure Time Data

This paper considers comparison of discrete failure time distributions when the survival time of interest measures elapsed time between two related events and observations on the occurrences of both events could be interval-censored. This kind of data is often referred to as doubly interval-censored failure time data. If the occurrence of the first event defining the survival time can be exactly observed, the data are usually referred to as interval-censored data. For the comparison problem based on interval-censored failure time data, Sun (1996) proposed a nonparametric test procedure. In this paper we generalize the procedure given in Sun (1996) to doubly interval-censored data case and the generalized test is evaluated by simulations.     

Female Relationships and Demographic Outcomes in Sub-Saharan Africa

This paper examines possible ways in which female relationships can affect demographic outcomes within the context of an extended family structure in sub-Saharan Africa. The level of collaboration and competition that exists among coresident women is likely to have an impact on fertility through changes in birth spacing and stopping behavior. In addition, the extent of collaboration could be a contributing factor in the survival chances of infants and young children. Given the multitude of ethnic groups found on the African continent, the paper also addresses the independent and interactive roles of culture. The paper ends with a discussion of theoretical and methodological implications for demographic research and suggestions for further study.     

适度规模经营何以可能？——基于农村老年人土地流转意愿的角度

基于全国12个省36个县1 104份基层调查数据,采用二元Logistic回归模型,从农村老年人土地转出意愿的角度考察了适度规模经营的可能性及其实现路径。结果表明：47%的农村老年人愿意转出土地,健康状况与农村老年人土地转出意愿有显著关系。由此得出：适度规模经营是可能的;优先解决农村老年人的“基本生存”问题,是促进农村老年人流转土地经营权、实现适度规模经营的第一步,而提高农村老年人的土地流转收益,才能让他们心甘情愿地流转土地经营权;改善农村代际关系、提高土地流转价格,将对促进农村土地流转、实现适度规模经营起到积极作用;优先促进70岁以上且健康状况较差的农村老年人转出土地,积极促进距离县城较近的农村老年人转出土地,将起到事半功倍的效果。     

风险资本异质性与被投高技术企业的长期绩效:以生存分析为基础的实证研究

联合风险投资中,不同的风险投资组合方式会给被投公司的发展前景带来重大影响,目前针对这一问题的研究尚有不足。从异质性视角出发,以生存分析方法探究风险投资组合异质性对被投高技术企业发展前景的影响。研究发现：若同一轮次投资于同一高技术公司的多个风投在活跃行业和活跃地点方面有较大差异,可能提高被投企业上市或被高价并购的风险率;风投在资本类型上的差异性将降低被投企业成功上市或被高价并购的风险率;风险投资异质性效应对处于不同融资轮次的高技术公司的影响程度不相同,处于发展后期的高技术公司更倾向于从风险投资的异质性组合中获益。     

在Kalman-Bucy滤波学习过程下的投资者生存能力分析

本文在投资者非完全理性框架下,基于Kalman-Bucy滤波学习过程给出了投资者理性和自信程度的定义,并基于此分析了不同投资者在市场中的生存和影响能力,并为实际市场中多类投资者共存的现象从学习过程的角度给予解释。研究结果表明,投资者在市场中的生存能力受其在学习过程中的理性和自信程度的双重影响。理性和自信程度都较高的投资者对市场把握较好,较容易在市场中生存,并对市场具有较大的影响。如果理性程度较高的投资者不自信,而理性程度不高的投资者自信度较高,那么在这种情况下没有哪类投资者对市场的把握相对准确,也就是说没有哪类投资者能将其他投资者逐出市场,即多类投资者共存于市场中。     

“山有多高，水有多高”——择塘村水务工程中的水权与林权

本文以“事件束”为切入点,遵循“整体生存伦理”的民族志认识论原则,把林权与水权置于当地人的生存智慧与道德表述中,从“他者”的视角全面审视林权与水权的历史实践,揭示林权与水权背后的民间法秩序。