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一般半参数共享脆弱性模型下的病例对照生存分析：伪完整似然方法AI 解读

In this work we deal with correlated failure time (age at onset) data arising from population-based, case-control studies, where case and control probands are selected by population-based sampling and an array of risk factor measures is collected for both cases and controls and their relatives. Parameters of interest are effects of risk factors on the failure time hazard function and within-family dependencies among failure times after adjusting for the risk factors. Due to…

一般半参数共享脆弱性模型的前瞻生存分析：伪完全似然方法AI 解读

We provide a simple estimation procedure for a general frailty model for the analysis of prospective correlated failure times. The large-sample properties of the proposed estimators of both the regression coefficient vector and the dependence parameter are described, and consistent variance estimators are given. A brief outline of the proofs is given. In a simulation study under the widely used gamma frailty model, our proposed approach was found to have essentially the same…

平稳高斯强相依过程参数最大似然估计的有效渐近展开AI 解读

We establish the validity of an Edgeworth expansion to the distribution of the maximum likelihood estimator of the parameter of a stationary, Gaussian, strongly dependent process. The result covers ARFIMA-type models, including fractional Gaussian noise. The method of proof consists of three main ingredients: (i) verification of a suitably modified version of Durbin's general conditions for the validity of the Edgeworth expansion to the joint density of the log-likelihood…

长程依赖下样本自相关函数的有效 Edgeworth 展开AI 解读

We prove in this paper the validity of an Edgeworth expansion to the joint distribution of the sample autocorrelations of a stationary Gaussian long memory process. The method of proof relies on a verification of the suitably modified conditions for the validity of a multivariate Edgeworth expansion of Durbin (1980, Biometrika 67, 311–333). A simulation study proves the expansion to be useful and accurate.

混合线性模型的小样本推断改进：Bartlett 校正与调整似然AI 解读

Summary The mixed linear model is a popular method for analysing unbalanced repeated measurement data. The classical statistical tests for parameters in this model are based on asymptotic theory that is unreliable in the small samples that are often encountered in practice. For testing a given fixed effect parameter with a small sample, we develop and investigate refined likelihood ratio (LR) tests. The refinements considered are the Bartlett correction and use of the…

ARFIMA 模型中基于似然的小样本推断AI 解读

The autoregressive fractionally integrated moving average (ARFIMA) model has become a popular approach for analyzing time series that exhibit long-range dependence. For the Gaussian case, there have been substantial advances in the area of likelihood-based inference, including development of the asymptotic properties of the maximum likelihood estimates and formulation of procedures for their computation. Small-sample inference, however, has not to date been studied. Here we…

含协变量的限制平均生存时间：方法改进与扩展AI 解读

Karrison has presented a method for covariate-adjusted comparison of two groups with respect to survival when the group effect is expected to not be of proportional hazards form. This article describes a simplified procedure for implementing Karrison's basic approach, along with an extended version designed to achieve robustness against misspecification in the underlying analytical model. A simulation study of these techniques is presented, and the techniques are illustrated…

含协变量的限制平均生存时间：方法简化与扩展AI 解读

Karrison has presented a method for covariate-adjusted comparison of two groups with respect to survival when the group effect is expected to not be of proportional hazards form. This article describes a simplified procedure for implementing Karrison's basic approach, along with an extended version designed to achieve robustness against misspecification in the underlying analytical model. A simulation study of these techniques is presented, and the techniques are illustrated…

治疗效果存在滞后时比较生存曲线的加权对数秩统计量AI 解读

In certain long-term treatment trials, one expects some lag period before the treatment is fully effective. This paper presents two weighted log rank type statistics designed to have good efficiency over a wide range of lags: a maximin efficiency robust statistic and a simplified version of this statistic. Both statistics can be computed as easily as the log rank statistic. Asymptotic efficiency calculations, supported by small sample simulations, show that the two proposed…

时变协变量效应的非参数生存分析：惩罚偏似然方法AI 解读

Techniques are developed for nonparametric analysis of data under a Cox-regression-like model permitting time-dependent covariate effects determined by a regression function $\beta_0(t)$. Estimators resulting from maximization of an appropriate penalized partial likelihood are shown to exist and a computational approach is outlined. Weak uniform consistency (with a rate of convergence) and pointwise asymptotic normality of the estimators are established under regularity…

治疗效果滞后时比较生存曲线的加权对数秩统计量AI 解读

In certain long-term treatment trials, one expects some lag period before the treatment is fully effective. This paper presents two weighted log rank type statistics designed to have good efficiency over a wide range of lags: a maximin efficiency robust statistic and a simplified version of this statistic. Both statistics can be computed as easily as the log rank statistic. Asymptotic efficiency calculations, supported by small sample simulations, show that the two proposed…