Reilly M
Department of Statistics, University College Dublin, Belfield, Ireland.
Am J Epidemiol. 1996 Jan 1;143(1):92-100. doi: 10.1093/oxfordjournals.aje.a008662.
The optimal allocation of available resources is the concern of every investigator in choosing a study design. The recent development of statistical methods for the analysis of two-stage data makes these study designs attractive for their economy and efficiency. However, little work has been done on deriving two-stage designs that are optimal under the kinds of constraints encountered in practice. The methods presented in this paper provide a means of deriving designs that will maximize precision for a fixed total budget or minimize the study cost necessary to achieve a desired precision. These optimal designs depend on the relative information content and the relative cost of gathering the first- and second-stage data. In place of the usual sample size calculations, the investigator can use pilot data to estimate the study size and second-stage sampling fractions. The gains in efficiency that can result from such carefully designed studies are illustrated here by deriving and implementing optimal designs using data from the Coronary Artery Surgery Study.
在选择研究设计时，可用资源的最优分配是每位研究者所关心的问题。用于分析两阶段数据的统计方法的最新发展，使得这些研究设计因其经济性和效率而颇具吸引力。然而，在推导实际中遇到的各种约束条件下最优的两阶段设计方面，所做的工作很少。本文提出的方法提供了一种推导设计的手段，这种设计能在固定的总预算下使精度最大化，或者使达到期望精度所需的研究成本最小化。这些最优设计取决于第一阶段和第二阶段数据的相对信息含量以及收集它们的相对成本。研究者可以使用试点数据来估计研究规模和第二阶段的抽样比例，以此取代通常的样本量计算。本文通过使用冠状动脉外科手术研究的数据推导并实施最优设计，来说明这种精心设计的研究可能带来的效率提升。
