Freidlin B, Zheng G, Li Z, Gastwirth J L
Biometric Research Branch, National Cancer Institute, Rockville, MD 20892, USA.
Hum Hered. 2002;53(3):146-52. doi: 10.1159/000064976.
The Cochran-Armitage trend test is commonly used as a genotype-based test for candidate gene association. Corresponding to each underlying genetic model there is a particular set of scores assigned to the genotypes that maximizes its power. When the variance of the test statistic is known, the formulas for approximate power and associated sample size are readily obtained. In practice, however, the variance of the test statistic needs to be estimated. We present formulas for the required sample size to achieve a prespecified power that account for the need to estimate the variance of the test statistic. When the underlying genetic model is unknown one can incur a substantial loss of power when a test suitable for one mode of inheritance is used where another mode is the true one. Thus, tests having good power properties relative to the optimal tests for each model are useful. These tests are called efficiency robust and we study two of them: the maximin efficiency robust test is a linear combination of the standardized optimal tests that has high efficiency and the MAX test, the maximum of the standardized optimal tests. Simulation results of the robustness of these two tests indicate that the more computationally involved MAX test is preferable.
Cochr an - Armitage趋势检验通常用作基于基因型的候选基因关联检验。对应于每个潜在的遗传模型,都有一组特定的分数分配给基因型,以使其功效最大化。当检验统计量的方差已知时,可以很容易地得到近似功效和相关样本量的公式。然而,在实际中,检验统计量的方差需要进行估计。我们给出了考虑到需要估计检验统计量方差的情况下,达到预先指定功效所需样本量的公式。当潜在的遗传模型未知时,如果使用适合一种遗传模式的检验而另一种模式才是真实模式,就可能会导致功效的大幅损失。因此,相对于每个模型的最优检验具有良好功效特性的检验是有用的。这些检验被称为效率稳健检验,我们研究其中两种:极大极小效率稳健检验是标准化最优检验的线性组合,具有较高效率;MAX检验是标准化最优检验中的最大值。这两种检验稳健性的模拟结果表明,计算量较大的MAX检验更可取。