论文检索

广义半线性模型的有效估计AI 解读

The generalized semilinear model (GSLIM) extends the generalized linear model by allowing the addition of an unknown smooth function to the predictor parameter, producing a semiparametric model. Some previously proposed score-based estimators for the parametric component in this model are not √n consistent. We propose efficient estimators for both the parametric and nonparametric components of the GSLIM. The estimator for the parametric component is the solution to an…

广义半线性模型的有效估计量AI 解读

The generalized semilinear model (GSLIM) extends the generalized linear model by allowing the addition of an unknown smooth function to the predictor parameter, producing a semiparametric model. Some previously proposed score-based estimators for the parametric component in this model are not √n consistent. We propose efficient estimators for both the parametric and nonparametric components of the GSLIM. The estimator for the parametric component is the solution to an…

异质且相互作用人群中的疾病侵袭率估计及 HIV 疫苗试验应用AI 解读

We describe models for infectious disease attack rates outside Aalen's multiplicative class and incorporating heterogeneity and interactions between subjects. Large-sample theory for the Nelson-Aalen estimator is developed, and its relevance examined in a simulation study. Planning for randomized, controlled clinical trials of prophylactic HIV vaccines partly motivated this work.

伪似然比检验统计量的渐近行为AI 解读

SUMMARY This paper concerns the asymptotic distribution of the likelihood ratio statistic T for testing H 0: θ = θ 0 based on the pseudolikelihood L(θ,ϕ^), where ϕ^ is a simple estimator of ϕ. We show that the asymptotic distribution of T under H 0 is a weighted sum of independent χ 1 2-variables where the weights involve the asymptotic joint covariance matrix of ϕ^ and the score function for θ. Some sufficient conditions are provided for the limiting distribution to be χ 2.…

利用部分指数模型估计多元均值参数AI 解读

SUMMARY A class of partly exponential models is proposed for the regression analysis of multivariate response data. The class is parameterized in terms of the response mean and a general shape parameter. It includes the generalized linear error model and exponential dispersion models as special cases. Maximum likelihood equations for mean parameters are shown to be of the same form as certain generalized estimating equations, and maximum likelihood estimates of mean and…

病例队列研究的渐近分布理论与效率结果AI 解读

A case-cohort design was recently proposed [Prentice (1986)] as a means of reducing cost in large epidemiologic cohort studies. A "pseudolikelihood" procedure was described for relative risk regression parameter estimation. This procedure involves covariate data only on subjects who develop disease and on a random subset of the entire cohort. In contrast, the usual partial likelihood estimation procedure requires covariate histories on the entire cohort. Accordingly, a…

非标准条件下最大似然估计与似然比检验的渐近性质AI 解读

Large sample properties of the likelihood function when the true parameter value may be on the boundary of the parameter space are described. Specifically, the asymptotic distribution of maximum likelihood estimators and likelihood ratio statistics are derived. These results generalize the work of Moran (1971), Chant (1974), and Chernoff (1954). Some of Chant's results are shown to be incorrect. The approach used in deriving these results follows from comments made by Moran…

稀疏数据下优势比同质性的检验AI 解读

Three tests for homogeneity of odds ratio for a series of 2 × 2 tables when the data are sparse are studied by means of Monte Carlo experiments. A score test, based on the assumption that the log odds ratios are generated from some unknown distribution, is shown to be more powerful than the other two. The original test of Zelen (1971), later corrected by Halperin, Ware, Byar et al. (1977), is also examined. It tends to be too liberal under the sparse data situation; however,…

摘要暂缺

稀疏数据下优势比同质性的检验AI 解读

Three tests for homogeneity of odds ratio for a series of 2 × 2 tables when the data are sparse are studied by means of Monte Carlo experiments. A score test, based on the assumption that the log odds ratios are generated from some unknown distribution, is shown to be more powerful than the other two. The original test of Zelen (1971), later corrected by Halperin, Ware, Byar et al. (1977), is also examined. It tends to be too liberal under the sparse data situation; however,…

具有时间不变协变量的二元纵向数据分析AI 解读

This paper considers extensions of logistic regression to the case where the binary outcome variable is observed repeatedly for each subject. We propose two working models that lead to consistent estimates of the regression parameters and of their variances under mild assumptions about the time dependence within each subject's data. The efficiency of the proposed estimators is examined. An analysis of stress in mothers with infants is presented to illustrate the proposed…

一般相对风险形式下 Cox 型回归模型的渐近分布理论AI 解读

The theory and application of the Cox (1972) failure time regression model has, almost without exception, assumed an exponential form for the dependence of the hazard function on regression variables. Other regression forms may be more natural or descriptive in some applications. For example, a linear relative risk regression model provides a convenient framework for studying epidemiologic risk factor interactions. This note uses the counting process formulation of Andersen…

对 Andersen 与 Gill《计数过程中的 Cox 回归模型：大样本研究》的评论AI 解读

In this issue Andersen and Gill (hereafter AG) present a stimulating development of asymptotic distribution theory for the Cox regression model with time-dependent covariates. They use a counting process formulation for the failure time data and martingale covergence results. This approach involves such conditions as $\sigma$-algebra right continuity and predictable, locally bounded, covariate processes. In this commentary we consider the implications of such assumptions for…