Increase in power through multivariate analyses
Increase in power through multivariate analyses
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DOI：
10.1023/a:1021669602220
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发表时间：
1998-09-01
影响因子：
2.6
通讯作者：
Fulker, DW
中科院分区：
文献类型：
--
作者：
Schmitz, S;Cherny, SS;Fulker, DW
检测遗传和环境影响的能力不仅随着样本量的增加而增加，而且还随着通过纵向和/或多变量设计的测量数量的增加而增加，如果这些测量结果彼此相关的话。针对具有不同遗传和环境参数的单变量到四变量情况进行了功率模拟。尽管受试者流失是大多数纵向研究的一个问题，但在许多情况下，可用能力的增益可能足以弥补这一缺点。在规划研究以检查遗传和环境影响方面，功效计算不仅应考虑样本量，还应考虑特定表型的测量数量及其相互关系。
Power to detect genetic and environmental influences increases not only with sample size but also with the number of measurements through longitudinal and/or multivariate designs, if those measurements correlate with each other. Power simulations are presented for uni- through quadrivariate cases, with differing genetic and environmental parameters. Even though subject attrition is a problem for most longitudinal studies, the gain in power available may more than make up for this shortcoming in many situations. In terms of planning studies to examine genetic and environmental influences, power calculations should not only consider sample size but number of measurements on particular phenotypes and their intercorrelations.