Julious Steven A, Owen Roger J
Medical Statistics Group, Health Services Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield S1 4DA, UK.
Pharm Stat. 2006 Jan-Mar;5(1):29-37. doi: 10.1002/pst.197.
One of the most important steps in the design of a pharmaceutical clinical trial is the estimation of the sample size. For a superiority trial the sample size formula (to achieve a stated power) would be based on a given clinically meaningful difference and a value for the population variance. The formula is typically used as though this population variance is known whereas in reality it is unknown and is replaced by an estimate with its associated uncertainty. The variance estimate would be derived from an earlier similarly designed study (or an overall estimate from several previous studies) and its precision would depend on its degrees of freedom. This paper provides a solution for the calculation of sample sizes that allows for the imprecision in the estimate of the sample variance and shows how traditional formulae give sample sizes that are too small since they do not allow for this uncertainty with the deficiency being more acute with fewer degrees of freedom. It is recommended that the methodology described in this paper should be used when the sample variance has less than 200 degrees of freedom.
药物临床试验设计中最重要的步骤之一是样本量的估计。对于优效性试验，样本量公式（为达到规定的检验效能）将基于给定的具有临床意义的差异和总体方差值。该公式通常在假定已知总体方差的情况下使用，而实际上总体方差是未知的，要用带有相关不确定性的估计值来代替。方差估计值将从早期类似设计的研究中得出（或从之前几项研究的总体估计中得出），其精度将取决于其自由度。本文提供了一种计算样本量的方法，该方法考虑了样本方差估计中的不精确性，并展示了传统公式给出的样本量过小的情况，因为它们没有考虑到这种不确定性，自由度越少，这种不足就越明显。建议当样本方差的自由度小于200时，使用本文所述的方法。
