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Notes on estimation in Poisson frequency data under an incomplete block crossover design

机译:不完全块交叉设计下泊松频率数据估计的注意事项

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摘要

For comparison of two experimental treatments with a placebo under an incomplete block crossover design, we develop the weighted-least-squares estimator (WLSE) and the conditional maximum likelihood estimator (CMLE) of the relative treatment effects in Poisson frequency data. We further develop the interval estimator based on the WLSE, the interval estimator based on the CMLE, the interval estimator based on the conditional-likelihood ratio test and the interval estimator based on the exact conditional distribution. Using Monte Carlo simulations, we find that all interval estimators developed here can perform well in a variety of situations. The exact interval estimator derived here can be especially of use when both the number of patients and the mean number of event occurrences are small in a trial. We use the data taken as part of a double-blind randomized crossover trial comparing salbutamol and salmeterol with a placebo with respect to the number of exacerbations in asthma patients to illustrate the use of these estimators. (C) 2016 Elsevier B.V. All rights reserved.
机译:为了比较不完全嵌段交叉设计下使用安慰剂的两种实验治疗,我们开发了泊松频率数据中相对治疗效果的加权最小二乘估计器(WLSE)和条件最大似然估计器(CMLE)。我们进一步开发了基于WLSE的间隔估计器,基于CMLE的间隔估计器,基于条件似然比检验的间隔估计器以及基于精确条件分布的间隔估计器。使用蒙特卡洛模拟,我们发现这里开发的所有区间估计器在各种情况下都能表现良好。当患者人数和平均事件发生次数在试验中都较小时,此处得出的精确间隔估计值尤其有用。我们使用作为沙丁胺醇和沙美特罗与安慰剂比较哮喘患者加重次数的双盲随机交叉试验的一部分数据,以说明这些估计量的使用。 (C)2016 Elsevier B.V.保留所有权利。

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