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首页> 外文期刊>Pharmaceutical statistics. >A recommended analysis for 2 × 2 crossover trials with baseline measurements.
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A recommended analysis for 2 × 2 crossover trials with baseline measurements.

机译：对于2×2基线试验的交叉试验的推荐分析。

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摘要

In many two-period, two-treatment (2 × 2) crossover trials, for each subject, a continuous response of interest is measured before and after administration of the assigned treatment within each period. The resulting data are typically used to test a null hypothesis involving the true difference in treatment response means. We show that the power achieved by different statistical approaches is greatly influenced by (i) the 'structure' of the variance-covariance matrix of the vector of within-subject responses and (ii) how the baseline (i.e., pre-treatment) responses are accounted for in the analysis. For (ii), we compare different approaches including ignoring one or both period baselines, using a common change from baseline analysis (which we advise against), using functions of one or both baselines as period-specific or period-invariant covariates, and doing joint modeling of the post-baseline and baseline responses with corresponding mean constraints for the latter. Based on theoretical arguments and simulation-based type I error rate and power properties, we recommend an analysis of covariance approach that uses the within-subject difference in treatment responses as the dependent variable and the corresponding difference in baseline responses as a covariate. Data from three clinical trials are used to illustrate the main points. Copyright ? 2014 John Wiley & Sons, Ltd.
机译：在许多两期，两次治疗（2×2）交叉试验中，对于每个受试者，在每个时期内在分配指定的治疗之前和之后都需要测量持续关注的反应。所得数据通常用于检验涉及治疗反应均值真实差异的零假设。我们表明，通过不同的统计方法获得的功效受（i）受试者内部响应向量的方差-协方差矩阵的“结构”以及（ii）基线（即预处理）响应的影响很大在分析中被考虑。对于（ii），我们比较了不同的方法，包括忽略一个或两个时期的基线，使用基线分析的共同变化（我们建议不要这样做），使用一个或两个基线的函数作为特定时期或不变时期的协变量，以及基线后和基线响应的联合建模，以及后者的相应平均约束。基于理论论据和基于仿真的I类错误率和功率特性，我们建议对协方差方法进行分析，该方法将受试者反应中的治疗差异作为因变量，并将基线反应的相应差异作为协变量。来自三个临床试验的数据用于说明要点。版权？ 2014 John Wiley＆Sons，Ltd.

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