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随机效应元分析的贝叶斯半参数模型AI 解读

In meta-analysis, there is an increasing trend to explicitly acknowledge the presence of study variability through random-effects models. That is, one assumes that for each study there is a study-specific effect and one is observing an estimate of this latent variable. In a random-effects model, one assumes that these study-specific effects come from some distribution, and one can estimate the parameters of this distribution, as well as the study-specific effects themselves.…

Cox模型中若干Bootstrap置信区间的比较AI 解读

We study bootstrap confidence intervals for three types of parameters in Cox's proportional hazards model: the regression parameter, the survival function at fixed time points, and the median survival time at fixed values of a covariate. Several types of bootstrap confidence intervals are studied, and the type of interval is determined by two factors. One factor is the method of drawing the bootstrap sample. We consider three such methods: (1) ordinary resampling from the…

Cox模型中随协变量变化的中位生存时间置信带AI 解读

Let ξp (x) be the pth quantile of the distribution of the life length of an individual with covariate vector x in the Cox model. We introduce an estimator ξp (x) of ξp (x) and develop several families of confidence bands for ξ(x) as a function of x. To construct one type of band, we proceed as follows. We show that as n → ∞, where n is the number of individuals in the study, ) converges weakly to a Gaussian process W(x) with a complicated covariance structure. We then…

二元回归中的变量测量误差：Berkson情形AI 解读

In binary regression, the predictor variables may be measured with error. The Berkson case of the errors-in-variables problem is considered, under which the values of the predictor variables are set by the experimenter but not achieved exactly. A particular model for this case is considered, with probit regression and normally distributed errors of observation. The regression parameters for intercept and slope are to be estimated. Two estimators are studied, the maximum…

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