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二元生存数据关联模型中的半参数推断AI 解读

Clayton's (1978) model for association in bivariate survival data is both of intrinsic importance and an interesting example of a semiparametric estimation problem, that is a problem where inference about a parameter is required in the presence of nuisance functions. We derive the asymptotic variance of Clayton's estimator, obtaining a simple explicit formula for uncensored data and indicating the modification required when the survival times are subject to arbitrary random…

摘要暂缺

右删失数据的关联秩检验AI 解读

Rank tests for association between a time variable and a continuous covariate, and between two time variables are given in the presence of censoring. In the first case, these tests are related to the semiparametric tests of Cox (1972) and Prentice (1978) but differ in that the covariate is replaced by a score computed from its rank. In the second case, the test statistic is again a simple inner product, which in the proportional hazards model reduces to the correlation…

(NOTE: Each chapter concludes with Problems and Complements, Notes, and References.) 1. Statistical Models, Goals, and Performance Criteria. Data, Models, Parameters, and Statistics. Bayesian Models. The Decision Theoretic Framework. Prediction. Sufficiency. Exponential Families. 2. Methods of Estimation. Basic Heuristics of Estimation. Minimum Contrast Estimates and Estimating Equations. Maximum Likelihood in Multiparameter Exponential Families. Algorithmic Issues. 3.…

生存时间数据的非参数贝叶斯分析AI 解读

Summary A Bayesian analysis of the semi-parametric regression and life model of Cox (1972) is given. The cumulative hazard function is modelled as a gamma process. Both estimation of the regression parameters and of the underlying survival distribution are considered. The results are compared to the results obtained by other approaches.