INTENTIONALLY INCOMPLETE LONGITUDINAL DESIGNS .1. METHODOLOGY AND COMPARISON OF SOME FULL SPAN DESIGNS
INTENTIONALLY INCOMPLETE LONGITUDINAL DESIGNS .1. METHODOLOGY AND COMPARISON OF SOME FULL SPAN DESIGNS
复制标题
DOI：
10.1002/sim.4780111411
复制
发表时间：
1992-10-01
影响因子：
2
通讯作者：
HELMS, RW
中科院分区：
文献类型：
--
作者：
HELMS, RW
纵向设计在医学研究和许多其他学科中都很重要。完整的纵向研究，在每个测量场合对每个受试者进行评估，通常非常昂贵，并促使寻找更有效的设计。最近发展的统计方法促进了有意不完全纵向设计的使用，这种设计有可能比完全设计更有效。混合模型提供了合适的数据分析工具。固定效应假设可以通过最近开发的检验统计量F(H)来检验。统计量的小样本非中心分布的精确近似值使功率计算可行。在回顾了一些纵向设计术语和混合模型符号的基础上，总结了F(H)的计算及其非中心分布的近似幂。这些方法被用于获得大量故意不完整的全跨度设计，这些设计比完整设计更强大和/或成本更低。讨论了不完全设计高效率的来源以及不完全设计对随机缺失数据的潜在脆弱性。
Longitudinal designs are important in medical research and in many other disciplines. Complete longitudinal studies, in which each subject is evaluated at each measurement occasion, are often very expensive and motivate a search for more efficient designs. Recently developed statistical methods foster the use of intentionally incomplete longitudinal designs that have the potential to be more efficient than complete designs. Mixed models provide appropriate data analysis tools. Fixed effect hypotheses can be tested via a recently developed test statistic, F(H). An accurate approximation of the statistic's small sample non-central distribution makes power computations feasible. After reviewing some longitudinal design terminology and mixed model notation, this paper summarizes the computation of F(H) and approximate power from its non-central distribution. These methods are applied to obtain a large number of intentionally incomplete full-span designs that are more powerful and/or less costly alternatives to a complete design. The source of the greater efficiency of incomplete designs and potential fragility of incomplete designs to randomly missing data are discussed.