Statistical considerations in clinical trial design with event-free survival as the primary efficacy endpoint

In late-phase confirmatory clinical trials in the oncology field, time-to-event (TTE) endpoints are commonly used as primary endpoints for establishing the efficacy of investigational therapies. Among these TTE endpoints, overall survival (OS) is always considered as the gold standard. However, OS data can take years to mature, and its use for measurement of efficacy can be confounded by the use of post-treatment rescue therapies or supportive care. Therefore, to accelerate the development process and better characterize the treatment effect of new investigational therapies, other TTE endpoints such as progression-free survival and event-free survival (EFS) are applied as primary efficacy endpoints in some confirmatory trials, either as a surrogate for OS or as a direct measure of clinical benefits. For evaluating novel treatments for acute myeloid leukemia, EFS has been gradually recognized as a direct measure of clinical benefits. However, the application of an EFS endpoint is still controversial mainly due to the debate surrounding definition of treatment failure (TF) events. In this article, we investigate the EFS endpoint with the most conservative definition for the timing of TF, which is Day 1 since randomization. Specifically, the corresponding non-proportional hazard pattern of the EFS endpoint is investigated with both analytical and numerical approaches.     

Economic Stress, Quality of Life, and Mortality for the Oldest-Old in China

China??s oldest old population is estimated to quadruple by 2050. Yet, poverty rate for the oldest old has been the highest among all age groups in China. This paper investigates the relationship between economic stress, quality of life, and mortality among the oldest-old in China. Both objective economic hardships and perceived economic strain are examined. We base our investigation on data drawn from the Chinese Longitudinal Healthy Longevity Survey conducted between 2000 and 2005. Our sample includes 10,972 men and women between the ages of 80 and 105 in 2000. The data show that about 16% of these oldest-old lived under economic stress in 2000. The risk factors that make one vulnerable to economic stress include age, being male, being widowed or never married, being a minority member, having no education, having no living children, and not having children as main source of income, and having no pension. Economic stress is negatively associated with indicators of quality of life, such as the quality of medical care and mental well-being. The poor quality of life contributes to the higher mortality rate for the oldest old who are under economic stress. Results also show that perceived economic strain increases the risk of mortality by 42% in rural areas, even after controlling for basic demographic characteristics, life style factors, and major health events.?For the rural oldest-old, having children as a main source of income and having access to pension alleviates the negative impact of economic hardship on mortality hazard by 23 and 66% respectively. However, in urban areas, economic stress has no direct impact on the hazard of mortality.     

Cross-Sectional and Longitudinal Associations of Categories of Physical Activities with Dimensions of Subjective Well-Being in Taiwanese Older Adults

Physical activity takes place in different social contexts such as leisure, home, and work. However, the differential associations of these distinct categories of activity with aspects of well-being have rarely been investigated. This study was designed to estimate independent associations of (a) leisure-time, (b) domestic and (c) work-related physical activities with subjective well-being in older adults. A cross-sectional survey was conducted in 2009 with 2,295 community-dwelling older adults aged 65 or older in Kaohsiung, Taiwan. Among them, 307 participants were selected for a 3-year follow-up study in 2012. The results based on cross-sectional and longitudinal analyses demonstrated that leisure-time physical activity, after multivariate adjustment, was positively associated with five dimensions of well-being, including ‘physical’, ‘psychological’, ‘independence’, ‘learning and growth’, and ‘social’ well-being. Household physical activity was positively associated only with ‘social’ well-being. Occupational physical activity was not related to any dimension of well-being. The study suggests that associations between physical activity and dimensions of subjective well-being during later life are dependent on the social context in which the activity takes place. This study indicates that physical activity taken as leisure has greatest potential to enhance the quality of life of older adults.     

大学生社会主义核心价值观的培育系统与路径——基于社会生态系统理论的视角

大学生是社会主义核心价值观培育的重要人群。基于社会生态系统理论对大学生社会主义核心价值观培育的各层级系统的研究认为,新形势下大学生社会主义核心价值观培育的实现路径应切合大学生对社会主义核心价值观培育的内在需求,建立大学生社会主义核心价值培育的"三位"生态系统,促进各级系统之间的相互融合,推动系统良性运行。     

儿童文学经典复译研究——以《爱丽丝漫游奇境记》为例

通过对青岛市儿童文学翻译市场进行调查研究,在对《爱丽丝漫游奇境记》的大量复译本进行分析的基础上,我们发现,众多儿童文学经典复译作品在秉承初译优点、取得不同程度进步的同时,也暴露出一些问题,比较普遍的是漏译、误译和文字中英夹杂、有失规范等问题,最关键的问题在于儿童文学翻译的文学性没有质的提高,没有从根本上超越初译。我们认为,儿童文学的复译应该遵循批判性借鉴和实质性超越的原则,真正实现其存在价值。     

为何少数族群的参与较少?——移民、教育以及选举程序对亚裔美国选民登记及投票的影响

美国黑人和白人在选举投票上的差异性一直备受学界关注,但是亚裔美国人参与投票率低这个问题却没有得到应有的重视。利用"当前人口调查中关于投票和登记的附录",笔者分析评估了对于亚裔美国人及其他少数族群投票率低的四种解释,即社会经济(socio-economic)解释、文化适应(acculturation)解释、差异性回报(differential return)解释、制度障碍(institutional barriers)解释。笔者运用一种统计学模型,能够同时对登记和投票进行评估,得出了四点结论:第一,社会经济解释在解释白人与亚裔美国人的差异性时,没有像解释白人与其他少数族群的差异时那么有说服力;第二,作为文化适应的两项重要指标——移民身份和居住时间——直接影响到亚裔美国人和拉美裔美国人的选民登记,但对其投票的影响甚微;第三,教育通常对参与投票有积极的影响,但是教育对亚裔美国人参与率的影响相对低于其他族群,尤其是白人;第四,制度障碍,尤其是对于选民登记的各种要求,不同比例地屏蔽了很多亚裔美国人,其次是拉美裔美国人,去参与最后的投票。本文的反事实分析(counterfactual analyses)表明,如果没有选民登记这项要求,亚裔美国人和白人在选民投票上将没有区别。     

Fibonacci helps to evacuate from a convex region in a grid network

This study considers an evacuation problem where the evacuees try to escape to the boundary of an affected area, which is convex, and a grid network is embedded in the area. The boundary is unknown to the evacuees and we propose an online evacuation strategy based on the Fibonacci sequence. This strategy is proved to have a competitive ratio of 19.5, which is better than the best previously reported result of 21.     

比较优势动态递减概率模型及检验

在比较优势的持续时间是随机变量的条件下,文章运用不确定性数学方法和规范方法,推出了比较优势递减定理,认为比较优势会随着时间增加而递减,具有发散效应,即比较优势不会被锁定.推出的比较优势“无记忆性”定理表明,各国遵循比较优势发展国际贸易是正确的,国际贸易会让各个国家自动寻找到适合本国的比较优势.通过定义比较优势逆转概率,运用实证方法进行研究,研究表明比较优势基本符合比较优势递减定理和“无记忆性”定理内容,认为中国传统劳动密集型优势在逐渐减小,产业结构调整非常成功,逐渐拥有资本密集型优势和技术密集型优势,产业结构越来越合理.     

Small area estimation strategies for large population surveys: a comparison of design and model-based methods

Small area estimation (SAE) concerns with how to reliably estimate population quantities of interest when some areas or domains have very limited samples. This is an important issue in large population surveys, because the geographical areas or groups with only small samples or even no samples are often of interest to researchers and policy-makers. For example, large population health surveys, such as Behavioural Risk Factor Surveillance System and Ohio Mecaid Assessment Survey (OMAS), are regularly conducted for monitoring insurance coverage and healthcare utilization. Classic approaches usually provide accurate estimators at the state level or large geographical region level, but they fail to provide reliable estimators for many rural counties where the samples are sparse. Moreover, a systematic evaluation of the performances of the SAE methods in real-world setting is lacking in the literature. In this paper, we propose a Bayesian hierarchical model with constraints on the parameter space and show that it provides superior estimators for county-level adult uninsured rates in Ohio based on the 2012 OMAS data. Furthermore, we perform extensive simulation studies to compare our methods with a collection of common SAE strategies, including direct estimators, synthetic estimators, composite estimators, and Datta GS, Ghosh M, Steorts R, Maples J.'s [Bayesian benchmarking with applications to small area estimation. Test 2011;20(3):574–588] Bayesian hierarchical model-based estimators. To set a fair basis for comparison, we generate our simulation data with characteristics mimicking the real OMAS data, so that neither model-based nor design-based strategies use the true model specification. The estimators based on our proposed model are shown to outperform other estimators for small areas in both simulation study and real data analysis.     

A revisit to test the equality of variances of several populations

We revisit the problem of testing homoscedasticity (or, equality of variances) of several normal populations which has applications in many statistical analyses, including design of experiments. The standard text books and widely used statistical packages propose a few popular tests including Bartlett's test, Levene's test and a few adjustments of the latter. Apparently, the popularity of these tests have been based on limited simulation study carried out a few decades ago. The traditional tests, including the classical likelihood ratio test (LRT), are asymptotic in nature, and hence do not perform well for small sample sizes. In this paper we propose a simple parametric bootstrap (PB) modification of the LRT, and compare it against the other popular tests as well as their PB versions in terms of size and power. Our comprehensive simulation study bursts some popularly held myths about the commonly used tests and sheds some new light on this important problem. Though most popular statistical software/packages suggest using Bartlette's test, Levene's test, or modified Levene's test among a few others, our extensive simulation study, carried out under both the normal model as well as several non-normal models clearly shows that a PB version of the modified Levene's test (which does not use the F-distribution cut-off point as its critical value), and Loh's exact test are the “best” performers in terms of overall size as well as power.