Lange Christoph, Laird Nan M
Department of Biostatistics, Harvard School of Public Health, Boston, MA, 02115, USA.
Am J Hum Genet. 2002 Sep;71(3):575-84. doi: 10.1086/342406. Epub 2002 Aug 12.
Using large-sample theory, we present a unified approach to power calculations for family-based association tests. Currently available methods for power calculations are restricted to special designs or require approximations or simulations. Our analytical approach to power calculations is broadly applicable in many settings. We discuss power calculations for two scenarios that have high practical relevance and in which power previously could only be assessed by simulation studies or by approximations: (1) studies using both affected and unaffected offspring and (2) studies with missing parental information. When the population prevalence is high, it can be worthwhile to genotype unaffected offspring. For many scenarios, high power can be achieved with reasonable sample sizes, even when no parental information is available.
利用大样本理论，我们提出了一种用于基于家系的关联检验功效计算的统一方法。目前可用的功效计算方法仅限于特殊设计，或者需要近似计算或模拟。我们的功效计算分析方法在许多情况下都具有广泛的适用性。我们讨论了两种具有高度实际相关性的情形下的功效计算，在这两种情形中，之前只能通过模拟研究或近似计算来评估功效：（1）使用患病和未患病后代的研究；（2）缺少父母信息的研究。当人群患病率较高时，对未患病后代进行基因分型可能是值得的。对于许多情形，即使没有父母信息，通过合理的样本量也可以实现高功效。
