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竞争风险子分布的比例风险模型AI 解读

With explanatory covariates, the standard analysis for competing risks data involves modeling the cause-specific hazard functions via a proportional hazards assumption. Unfortunately, the cause-specific hazard function does not have a direct interpretation in terms of survival probabilities for the particular failure type. In recent years many clinicians have begun using the cumulative incidence function, the marginal failure probabilities for a particular cause, which is…

生存数据的组间变异检验AI 解读

When survival data can be divided into natural groups, such as in a clinical trial with patients from a number of different institutions, the question arises whether effects are different for the different groups. For situations where one is concerned with a random pattern of variation over groups, this article proposes testing the null hypothesis of no variation using statistics based on the sums of martingale residuals over subjects within groups. These tests are closely…

生存数据中组间变异的检验AI 解读

When survival data can be divided into natural groups, such as in a clinical trial with patients from a number of different institutions, the question arises whether effects are different for the different groups. For situations where one is concerned with a random pattern of variation over groups, this article proposes testing the null hypothesis of no variation using statistics based on the sums of martingale residuals over subjects within groups. These tests are closely…

将疾病进展信息纳入生存分析的核方法AI 解读

This paper considers incorporating information on disease progression in the analysis of survival. A three-state model is assumed, with the distribution of each transition estimated separately. The distribution of survival following progression can depend on the time of progression. Kernel methods are used to give consistent estimators under general forms of dependence. The estimators for the individual transitions are then combined into an overall estimator of the survival…

将疾病进展信息纳入生存分析的核方法AI 解读

This paper considers incorporating information on disease progression in the analysis of survival. A three-state model is assumed, with the distribution of each transition estimated separately. The distribution of survival following progression can depend on the time of progression. Kernel methods are used to give consistent estimators under general forms of dependence. The estimators for the individual transitions are then combined into an overall estimator of the survival…

利用样条灵活分析生存数据：乳腺癌预后应用AI 解读

In this article some flexible methods for modeling censored survival data using splines are applied to the problem of modeling the time to recurrence of breast cancer patients. The basic idea is to use fixed knot splines with a fairly modest number of knots to model aspects of the data, and then to use penalized partial likelihood to estimate the parameters of the model. Test statistics are proposed which are analogs of those used in traditional likelihood analysis, and…

比较竞争风险累积发生率的一类 K 样本检验AI 解读

In this paper, for right censored competing risks data, a class of tests developed for comparing the cumulative incidence of a particular type of failure among different groups. The tests are based on comparing weighted averages of the hazards of the subdistribution for the failure type of interest. Asymptotic results are derived by expressing the statistics in terms of counting processes and using martingale central limit theory. It is proposed that weight functions very…

删失生存数据的拟合优度检验AI 解读

The problem of testing the underlying distribution in a general regression model is considered when the data are right censored. It is proposed that tests be based on efficient scores from a certain class of parametric alternatives. The connection between tests based on the scores and more traditional approaches using empirical distribution functions is explored. Neyman's smooth test is extended to allow for censored data.

回归模型误差正态性的检验AI 解读

It was shown by Pierce & Kopecky (1979) that tests of normality appropriate for the identically distributed case are asymptotically valid when computed from residuals in regression situations. Numerical results based on simulation are given here to study the adequacy of this result for sample sizes of 20 and 40. The Shapiro-Wilk and Anderson-Darling tests are found to be quite adequate for n = 20 in typical simple linear regression situations, and for n = 40 in certain…