Nonparametric Tests for Stratum Effects in the Cox Model

Thispaper considers the stratified proportional hazards model witha focus on the assessment of stratum effects. The assessmentof such effects is often of interest, for example, in clinicaltrials. In this case, two relevant tests are the test of stratuminteraction with covariates and the test of stratum interactionwith baseline hazard functions. For the test of stratum interactionwith covariates, one can use the partial likelihood method (Kalbfleischand Prentice, 1980; Lin, 1994). For the test of stratum interactionwith baseline hazard functions, however, there seems to be noformal test available. We consider this problem and propose aclass of nonparametric tests. The asymptotic distributions ofthe tests are derived using the martingale theory. The proposedtests can also be used for survival comparisons which need tobe adjusted for covariate effects. The method is illustratedwith data from a lung cancer clinical trial.     

A method of computing the marital composition of the population between population censuses

A method for calculating the marital status distribution of the population of the USSR between censuses is outlined. The method is based on the use of population census and vital statistics data.     

在普通箱式炉中进行气体软氮化的研究

本文论述了以甲酰胺为渗剂,在普通箱式电炉中,对3 Cr 2 W 8 V 等钢进行气体软氮化的研究。成功地解决了3 Cr 2 W 8 V 钢压铸模热处理变形及模具在使用中的粘模问题。提高了模具的使用寿命。     

Convective Filmwise Condensation of R-11 inside a Vertical Tube

Partial condensation of refrigerant R-11 was experimentally and theoretically studied. The test apparatus consisted of two concentric tubes, with the vapor flowing downward in the inner tube and the cooling water in the annular space in countercurrent direction. By using the available dimensionless correlation, the mean heat transfer coefficient of the cooling water was determined, and then the mean condensationheat transfer coefficient was calculated from the overall heat transfer coefficient.The model of a homogeneous two-phase mixture of liquid and vapor, and Prandtl's principle of analogy between the momentum and heat transfer were used to establish the type of the correlation. Adopting the methods of the gradually linear regression and F-level evidence testing, the present paper proposed the dimensionless correlation to predict the relationship among the mean Nusselt number, Prandtl number, Kutateladze number and the dimensionless tube length.     

统计学的解释力——统计解释世界

从决定论到统计分析方法的广泛应用,再到非线性(混沌)理论,随机性与决定论之间矛盾吗?不确定性与确定性之间的相互转换是否仅限于逻辑上的推演?平均到底意味着什么?基于假设检验的结论是脆弱的吗?可为什么当模型通过各种统计检验之后我们并没有表现出来应有的沮丧?反倒是原假设被拒绝应该自信的时候,却有些垂头丧气.     

运用改进的粒度调节方法估计信用组合风险

文章在建立了信用风险单因素模型后,将信用风险用系统风险和特质风险之和表示.在计算特质风险时,当信用组合内资产规模较小时,Gonty提出的粒度调节方法将会低估组合VaR,而高估一致性风险量度——预期短缺ES.文章利用Taylor展开式改进的粒度调节方法,提高组合内资产规模较小时估计ES的准确性,模拟结果显示改进方法的有效性.     

Analysis of quality-of-life adjusted failure time data in the presence of competing, possibly informative, censoring mechanisms

We derive estimators of the mean of a function of a quality-of-life adjusted failure time, in the presence of competing right censoring mechanisms. Our approach allows for the possibility that some or all of the competing censoring mechanisms are associated with the endpoint, even after adjustment for recorded prognostic factors, with the degree of residual association possibly different for distinct censoring processes. Our methods generalize from a single to many censoring processes and from ignorable to non-ignorable censoring processes.     

A simple two-stage design for quantitative responses with application to a study in diabetic neuropathic pain

Two-stage designs offer substantial advantages for early phase II studies. The interim analysis following the first stage allows the study to be stopped for futility, or more positively, it might lead to early progression to the trials needed for late phase II and phase III. If the study is to continue to its second stage, then there is an opportunity for a revision of the total sample size. Two-stage designs have been implemented widely in oncology studies in which there is a single treatment arm and patient responses are binary. In this paper the case of two-arm comparative studies in which responses are quantitative is considered. This setting is common in therapeutic areas other than oncology. It will be assumed that observations are normally distributed, but that there is some doubt concerning their standard deviation, motivating the need for sample size review. The work reported has been motivated by a study in diabetic neuropathic pain, and the development of the design for that trial is described in detail.     

Models for the analysis of C-reactive protein in statin trials

Elevation in C-reactive protein (CRP) is an independent risk factor for cardiovascular disease progression and levels are reduced by treatment with statins. However, on-treatment CRP, given baseline CRP and treatment, is not normally distributed and outliers exist even when transformations are applied. Although classical non-parametric tests address some of these issues, they do not enable straightforward inclusion of covariate information. The aims of this study were to produce a model that improved efficiency and accuracy of analysis of CRP data. Estimation of treatment effects and identification of outliers were addressed using controlled trials of rosuvastatin. The robust statistical technique of MM-estimation was used to fit models to data in the presence of outliers and was compared with least-squares estimation. To develop the model, appropriate transformations of the response and baseline variables were selected. The model was used to investigate how on-treatment CRP related to baseline CRP and estimated treatment effects with rosuvastatin. On comparing least-squares and MM-estimation, MM-estimation was superior to least-squares estimation in that parameter estimates were more efficient and outliers were clearly identified. Relative reductions in CRP were higher at higher baseline CRP levels. There was also evidence of a dose-response relationship between CRP reductions from baseline and rosuvastatin. Several large outliers were identified, although there did not appear to be any relationships between the incidence of outliers and treatments. In conclusion, using robust estimation to model CRP data is superior to least-squares estimation and non-parametric tests in terms of efficiency, outlier identification and the ability to include covariate information.