论文标题
在广义线性模型中的分数测试改进的样本量计算方法
An improved sample size calculation method for score tests in generalized linear models
论文作者
论文摘要
Self and Mauritsen（1988）在连续替代方案下，在广义线性模型中开发了一个样本量确定程序。当效果大小较大时，其性能可能会恶化。我们提出了对自我mauritsen方法的修改，该方法考虑了零假设和替代假设下的分数统计量的方差，并将该方法扩展到非劣效试验。采用修改方法来计算优势和非劣效试验中的逻辑回归和负二项式回归的样本量。我们进一步解释了为什么Zhu和Lakkis最近得出的公式倾向于低估负二项式回归所需的样本量。数值示例用于证明该方法的准确性。
Self and Mauritsen (1988) developed a sample size determination procedure for score tests in generalized linear models under contiguous alternatives. Its performance may deteriorate when the effect size is large. We propose a modification of the Self-Mauritsen method by taking into account of the variance of the score statistic under both the null and alternative hypotheses, and extend the method to noninferiority trials. The modified approach is employed to calculate the sample size for the logistic regression and negative binomial regression in superiority and noninferiority trials. We further explain why the formulae recently derived by Zhu and Lakkis tend to underestimate the required sample size for the negative binomial regression. Numerical examples are used to demonstrate the accuracy of the proposed method.
