Patel H I, Rowe E
Clinical and Scientific Affairs, Central Research Division Pfizer, Inc., New York, New York 10017-5755, USA.
J Biopharm Stat. 1999 May;9(2):339-50. doi: 10.1081/BIP-100101180.
Assuming a linear growth curve model under a suitable link function, we compute the sample size for comparing two treatment groups when the repeated measurements marginally follow exponential family distributions. From the treatment profiles of the chosen link function, we compute the common intercept beta0 and the regression slopes beta1 and beta2 to define delta = beta1 - beta2, the difference to be detected, under a specified alternative hypothesis. The dispersion matrices of the generalized estimating equations estimators are obtained under the null and alternative hypotheses using a suitable working correlation matrix. We compute the sample size assuming that delta is asymptotically normal. Details are worked out for repeated measures designs with binary and count data along with numerical examples.
假设在合适的连接函数下有一个线性增长曲线模型，当重复测量近似服从指数族分布时，我们计算用于比较两个治疗组的样本量。根据所选连接函数的治疗概况，我们计算共同截距β0以及回归斜率β1和β2，以在特定备择假设下定义要检测的差异δ = β1 - β2。使用合适的工作相关矩阵在原假设和备择假设下获得广义估计方程估计量的离散矩阵。我们假设δ渐近正态来计算样本量。针对具有二元和计数数据的重复测量设计以及数值示例详细阐述了具体细节。
