Boehnke M, Greenberg D A
Am J Hum Genet. 1984 Nov;36(6):1298-308.
Cannings and Thompson suggested conditioning on the phenotypes of the probands to correct for ascertainment in the analysis of pedigree data. The method assumes single ascertainment and can be expected to yield asymptotically biased parameter estimates except in this specific case. However, because the method is easy to apply, we investigated the degree of bias in the more typical situation of multiple ascertainment, in the hope that the bias might be small and that the method could be applied more generally. To explore the utility of conditioning on probands to correct for multiple ascertainment, we calculated the asymptotic value of the segregation ratio for two versions of the simple Mendelian segregation model on sibship data. For both versions, we found that this asymptotic value decreased approximately linearly as the ascertainment probability increased. When ascertainment was complete, the segregation-ratio estimates were zero, not just asymptotically but for finite sample size as well. In some cases, conditioning on probands actually resulted in greater parameter bias than no ascertainment correction at all. These results hold for a variety of sibship-size distributions, several modes of inheritance, and a wide range of population prevalences of affected individuals.
坎宁斯和汤普森建议在分析系谱数据时，以先证者的表型为条件进行校正，以解决确定偏倚问题。该方法假定为单一确定，并且除了在这种特定情况下，预计会产生渐近有偏的参数估计。然而，由于该方法易于应用，我们研究了在更典型的多重确定情况下的偏倚程度，希望偏倚可能较小，并且该方法可以更广泛地应用。为了探索以先证者为条件进行校正以解决多重确定问题的效用，我们计算了基于同胞数据的两种简单孟德尔分离模型版本的分离比的渐近值。对于这两个版本，我们发现随着确定概率的增加，这个渐近值大致呈线性下降。当确定是完全的时，分离比估计值为零，不仅是渐近的，对于有限样本量也是如此。在某些情况下，以先证者为条件实际上导致的参数偏倚比根本不进行确定校正时更大。这些结果适用于各种同胞规模分布、几种遗传模式以及受影响个体的广泛人群患病率。
