Team Biostatistics and Big Medical Data, IDA Lab Salzburg, Paracelsus Medical University, Salzburg, Austria.
Department of Research and Innovation, Paracelsus Medical University, Salzburg, Austria.
Biom J. 2024 Jan;66(1):e2200236. doi: 10.1002/bimj.202200236. Epub 2023 Mar 8.
Ordinal data in a repeated measures design of a crossover study for rare diseases usually do not allow for the use of standard parametric methods, and hence, nonparametric methods should be considered instead. However, only limited simulation studies in settings with small sample sizes exist. Therefore, starting from an Epidermolysis Bullosa simplex trial with the above-mentioned design, a rank-based approach using the R package nparLD and different generalized pairwise comparisons (GPC) methods were compared impartially in a simulation study. The results revealed that there was not one single best method for this particular design, because a trade-off exists between achieving high power, accounting for period effects, and for missing data. Specifically, nparLD as well as the unmatched GPC approaches do not address crossover aspects, and the univariate GPC variants partly ignore the longitudinal information. The matched GPC approaches, on the other hand, take the crossover effect into account in the sense of incorporating the within-subject association. Overall, the prioritized unmatched GPC method achieved the highest power in the simulation scenarios, although this may be due to the specified prioritization. The rank-based approach yielded good power even at a sample size of , whereas the matched GPC method could not control the type I error.
在罕见病交叉研究的重复测量设计中，有序数据通常不允许使用标准参数方法，因此应考虑使用非参数方法。然而，仅有少量的模拟研究在小样本量的情况下存在。因此，从具有上述设计的单纯型大疱性表皮松解症试验出发，在模拟研究中，使用 R 包 nparLD 和不同的广义成对比较（GPC）方法，公正地比较了基于等级的方法。结果表明，对于这种特殊的设计，不存在一种单一的最佳方法，因为在实现高功效、考虑周期效应和处理缺失数据之间存在权衡。具体来说，nparLD 以及非匹配的 GPC 方法没有解决交叉问题，而单变量 GPC 变体部分忽略了纵向信息。另一方面，匹配的 GPC 方法在一定程度上考虑了交叉效应，即包含了个体内的关联。总的来说，在模拟场景中，优先的非匹配 GPC 方法实现了最高的功效，尽管这可能是由于指定的优先级。基于等级的方法即使在样本量为 的情况下也能获得良好的功效，而匹配的 GPC 方法无法控制 I 型错误。
