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2×2交叉试验中个体内变异的精确推断AI 解读

The comparison of primary interest in a 2 × 2 crossover trial typically concerns the effect of the treatments, say A and B, on the mean response level. This article deals with another important aspect, namely the within-subject response variability under A and B. Differences in drug formulation and/or administration may lead to considerable differences in within-subject variability, whatever the difference in terms of mean level. Consideration of both these aspects may,…

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左截断和／或右删失数据的精确 Kolmogorov 型检验AI 解读

The tests proposed in this article are natural generalizations of the ordinary Kolmogorov—Smirnov one-sample tests based on the product-limit estimator. They can be used with left-truncated and/or right-censored data and, as the ordinary tests, they have the nice properties of being valid for any sample size and any underlying distribution specified by the null hypothesis. The acceptance region for the product-limit estimator consists of a Kolmogorov—Smirnov-type region that…

左截断和／或右删失数据的精确 Kolmogorov 型检验AI 解读

The tests proposed in this article are natural generalizations of the ordinary Kolmogorov—Smirnov one-sample tests based on the product-limit estimator. They can be used with left-truncated and/or right-censored data and, as the ordinary tests, they have the nice properties of being valid for any sample size and any underlying distribution specified by the null hypothesis. The acceptance region for the product-limit estimator consists of a Kolmogorov—Smirnov-type region that…

一般情形下未来样本中位数的非参数预测区间AI 解读

This article deals with nonparametric prediction intervals for the median(s) of a future sample of arbitrary size without any assumption about the parent distribution. The best possible distribution-free lower bounds for the relevant coverage probabilities are derived. Furthermore, these sharp lower bounds are given in terms of lower tail probabilities of hypergeometric and binomial distributions for which extensive tables and good approximations are available.