Simultaneous confidence intervals for multiple comparisons among expected values of log-normal variables
Simultaneous confidence intervals for multiple comparisons among expected values of log-normal variables
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DOI：
10.1016/j.csda.2012.08.011
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发表时间：
2013-02
期刊：
影响因子：
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通讯作者：
F. Schaarschmidt
中科院分区：
文献类型：
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作者：
F. Schaarschmidt
在生物学和医学研究中，连续的、严格正的、右偏的数据（可能具有异质方差）是常见的，并且可以用对数正态分布来描述。在单向布局中涉及多个处理的实验中，处理之间的各种多重比较集和相应的同时置信区间可能会引起兴趣。重点是治疗期望值的多重对比。以前发表的基于正态近似和广义关键量的方法被扩展到多重对比的情况。在模拟研究中对这些方法进行了评估，该研究包括与对照组的比较，所有的两两比较，以及为了说明更一般的多种对比类型，非标准类型的对比矩阵。推荐使用基于广义枢纽量的方法，因为它在同时覆盖概率方面优于所有其他方法，并且i型误差在上下置信区间之间几乎均匀分布。发现基于正态近似的方法对于定向i型误差是非常自由和有偏差的。并以药学研究为例对这些方法进行了说明。
In biological and medical research, continuous, strictly positive, right-skewed data, possibly with heterogeneous variances, are common, and can be described by log-normal distributions. In experiments involving multiple treatments in a one-way layout, various sets of multiple comparisons among the treatments and corresponding simultaneous confidence intervals can be of interest. The focus is on multiple contrasts of the expected values of the treatments. Previously published methods based on normal approximations and generalized pivotal quantities are extended to the case of multiple contrasts. These methods are evaluated in a simulation study that involves comparisons to a control group, all pairwise comparisons and, to illustrate more general multiple contrast types, a non-standard type of contrast matrix. A method based on generalized pivotal quantities is recommended because it is superior to all other methods in terms of simultaneous coverage probability and because the type-I-errors are distributed almost equally between lower and upper confidence bounds. Methods based on normal approximations are found to be very liberal and biased with respect to directional type-I-errors. These methods are illustrated with an example from pharmaceutical research.