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多元失效时间数据的边际回归模型AI 解读

In this article we propose a general Cox-type regression model to formulate the marginal distributions of multivariate failure time data. This model has a nested structure in that it allows different baseline hazard functions among distinct failure types and imposes a common baseline hazard function on the failure times of the same type. We prove that the maximum “quasi-partial-likelihood” estimator for the vector of regression parameters under the independence working…

计数过程一般加性—乘性风险模型的半参数分析AI 解读

The additive-multiplicative hazard model specifies that the hazard function for the counting process associated with a multidimensional covariate process $Z = (W^T, X^T)^T$ takes the form of $\lambda(t\mid Z) = g\{\beta^T_0 W(t)\} + \lambda_0(t)h\{\gamma^T_0X(t)\}$, where $\theta_0 = (\beta^T_0, \gamma^T_0)^T$ is a vector of unknown regression parameters, $g$ and $h$ are known link functions and $\lambda_0$ is an unspecified "baseline hazard function." In this paper, we…

加性风险模型的半参数分析AI 解读

In contrast to the proportional hazards model, the additive risk model specifies that the hazard function associated with a set of possibly time-varying covariates is the sum of, rather than the product of, the baseline hazard function and the regression function of covariates. This formulation describes a different aspect of the association between covariates and the failure time than the proportional hazards model, and is more plausible than the latter for many…

摘要暂缺

协变量测量不完整时的Cox回归AI 解读

This article provides a general solution to the problem of missing covariate data under the Cox regression model. The estimating function for the vector of regression parameters is an approximation to the partial likelihood score function with full covariate measurements and reduces to the pseudolikelihood score function of Self and Prentice in the special setting of case-cohort designs. The resulting parameter estimator is consistent and asymptotically normal with a…

单变量删失下二元生存函数的简单非参数估计量AI 解读

In the presence of univariate censoring, the bivariate survival function of paired failure times can be expressed as the ratio of the bivariate at-risk probability to the survival function of the censoring time. The use of this natural representation yields a very simple nonparametric estimator for the bivariate survival curve. The estimator is strongly consistent and, upon proper normalization, converges weakly to a zero-mean Gaussian process with an easily estimated…

单变量删失下二元生存函数的简单非参数估计AI 解读

In the presence of univariate censoring, the bivariate survival function of paired failure times can be expressed as the ratio of the bivariate at-risk probability to the survival function of the censoring time. The use of this natural representation yields a very simple nonparametric estimator for the bivariate survival curve. The estimator is strongly consistent and, upon proper normalization, converges weakly to a zero-mean Gaussian process with an easily estimated…

利用鞅残差累积和检验 Cox 模型AI 解读

This paper presents a new class of graphical and numerical methods for checking the adequacy of the Cox regression model. The procedures are derived from cumulative sums of martingale-based residuals over follow-up time and/or covariate values. The distributions of these stochastic processes under the assumed model can be approximated by zero-mean Gaussian processes. Each observed process can then be compared, both visually and analytically, with a number of simulated…

用加速寿命模型调整协变量的序贯对数秩检验AI 解读

This paper presents a simple sequential method for comparing two treatments in randomized clinical trials which allows for the adjustment of other covariates with the accelerated life model. The new procedure is the same as the ordinary sequential log rank test except that the test statistic is calculated on an ‘adjusted’ time scale. This covariate adjustment can lead to more efficient designs of group sequential trials especially when the effects of covariates being…

摘要暂缺

利用加速寿命模型调整协变量的序贯对数秩检验AI 解读

This paper presents a simple sequential method for comparing two treatments in randomized clinical trials which allows for the adjustment of other covariates with the accelerated life model. The new procedure is the same as the ordinary sequential log rank test except that the test statistic is calculated on an ‘adjusted’ time scale. This covariate adjustment can lead to more efficient designs of group sequential trials especially when the effects of covariates being…

多组临床试验中针对有序备择的非参数序贯检验AI 解读

In a multiple-armed clinical trial where one agent is administered at several dose levels or where each treatment regimen is formed by adding more agents to the preceding combination, it is desirable to use test statistics that are sensitive to alternatives of stochastically ordered distributions. Liu et al (1992) recently developed a class of such test statistics by taking linear combinations of the familiar two-sample weighted log rank statistics. In the present paper, we…

基于一类参数估计量的 Cox 回归拟合优度分析AI 解读

In this article we propose a class of estimation functions for the vector of regression parameters in the Cox proportional hazards model with possibly time-dependent covariates by incorporating the weight functions commonly used in weighted log-rank tests into the partial likelihood score function. The resulting estimators behave much like the conventional maximum partial likelihood estimator in that they are consistent and asymptotically normal. When the Cox model is…

含不完整多元观测的临床试验非参数序贯检验AI 解读

SUMMARY This paper addresses sequential testing in randomized clinical trials with multiple endpoints. Patients enter treatments serially and are subject to random loss to followup. The endpoints of interest may be time-to-event variables or other quantitative measurements. The proposed test statistic at a given look is a weighted sum of the linear rank statistics with respect to the marginal distributions of the multiple endpoints. The weights can be chosen to maximize…

多变量观测不完整的临床试验中的非参数序贯检验AI 解读

This paper addresses sequential testing in randomized clinical trials with multiple endpoints. Patients enter treatments serially and are subject to random loss to followup. The endpoints of interest may be time-to-event variables or other quantitative measurements. The proposed test statistic at a given look is a weighted sum of the linear rank statistics with respect to the marginal distributions of the multiple endpoints. The weights can be chosen to maximize asymptotic…

基于秩检验的删失生存数据线性回归分析AI 解读

Recently linear rank statistics with censored data have been used as the estimating functions for the regression parameters in the linear model with an unspecified error distribution. The resulting rank estimators are consistent and asymptotically normal. However, the asymptotic variances of these estimators are complicated and are difficult to estimate well with censored data. In this paper, we propose some simple methods for making inference about a subset of the…

数据依赖型治疗分配规则下的统计推断AI 解读

In comparing two treatments with dichotomous responses, the randomized play-the-winner rule (Wei and Durham 1978) tends to assign more study subjects to the better treatment. For ethical reasons, this property is desirable for studies on human subjects. The randomized play-the-winner rule, which is a modification of Zelen's play-the-winner rule (Zelen 1969), is not deterministic and is less vulnerable to experimental bias than other adaptive designs. Recently, this design…

基于秩检验的删失生存数据线性回归分析AI 解读

Recently linear rank statistics with censored data have been used as the estimating functions for the regression parameters in the linear model with an unspecified error distribution. The resulting rank estimators are consistent and asymptotically normal. However, the asymptotic variances of these estimators are complicated and are difficult to estimate well with censored data. In this paper, we propose some simple methods for making inference about a subset of the…

Cox 比例风险模型的稳健推断AI 解读

We derive the asymptotic distribution of the maximum partial likelihood estimator β for the vector of regression coefficients β under a possibly misspecified Cox proportional hazards model. As in the parametric setting, this estimator β converges to a well-defined constant vector β*. In addition, the random vector n 1/2(β – β*) is asymptotically normal with mean 0 and with a covariance matrix that can be consistently estimated. The newly proposed robust covariance matrix…

通过边际分布建模分析多元不完整失效时间数据AI 解读

Many survival studies record the times to two or more distinct failures on each subject. The failures may be events of different natures or may be repetitions of the same kind of event. In this article, we consider the regression analysis of such multivariate failure time observations. Each marginal distribution of the failure times is formulated by a Cox proportional hazards model. No specific structure of dependence among the distinct failure times on each subject is…