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依赖数据下的优势比推断AI 解读

When data can be presented as a series of k 2×2 tables with cell counts (xi ,ni−xi, yi, mi−yi), it is often assumed that xi and yi are binomially distributed. This paper deals with inference for the common odds ratio Ψ when the binomial assumption is invalid. When k increases, the consistency and asymptotic normality of the Mantel & Haenszel (1959) estimator is derived. The conditional maximum likelihood estimator is shown to be inconsistent and the asymptotic bias is…

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…

条件似然方法的渐近效率AI 解读

This paper concerns the efficiency of the conditional likelihood method for inference in models which include nuisance parameters. A new concept of ancillarity, asymptotic weak ancillarity, is introduced. It is shown that the conditional maximum likelihood estimator and the conditional score test of θ, the parameter of interest, are asymptotically equivalent to their unconditional counterparts, and hence are asymptotically efficient, provided that the conditioning statistic…

条件似然方法的渐近效率AI 解读

SUMMARY This paper concerns the efficiency of the conditional likelihood method for inference in models which include nuisance parameters. A new concept of ancillarity, asymptotic weak ancillarity, is introduced. It is shown that the conditional maximum likelihood estimator and the conditional score test of 0, the parameter of interest, are asymptotically equivalent to their unconditional counterparts, and hence are asymptotically efficient, provided that the conditioning…

存在干扰参数时的信息与辅助性AI 解读

This note shows that concepts of ancillarity in the presence of a nuisance parameter suggested by Andersen (1970) and Basawa (1981) are equivalent for exponential families of distributions. Some illustrative examples are given and the relation to Fisher's information is discussed.

存在干扰参数时的信息与辅助性AI 解读

This note shows that concepts of ancillarity in the presence of a nuisance parameter suggested by Andersen (1970) and Basawa (1981) are equivalent for exponential families of distributions. Some illustrative examples are given and the relation to Fisher's information is discussed.