Using simulation studies to evaluate statistical methods
Using simulation studies to evaluate statistical methods
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DOI：
10.1002/sim.8086
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发表时间：
2019-05-20
影响因子：
2
通讯作者：
Crowther, Michael J.
中科院分区：
文献类型：
--
作者：
Morris, Tim P.;White, Ian R.;Crowther, Michael J.
模拟研究是通过伪随机抽样创建数据的计算机实验。模拟研究的一个关键优势是能够理解统计方法的行为，因为一些真相（通常是一些感兴趣的参数）是从生成数据的过程中得知的。这允许我们考虑方法的属性，例如偏差。虽然被广泛使用，但模拟研究往往设计、分析和报告得很差。本教程概述了使用模拟研究的基本原理，并为设计、执行、分析、报告和演示提供了指导。特别是，本教程提供了一个结构化的方法规划和报告模拟研究，其中包括定义目标，数据生成机制，estimands，方法和性能指标（ADEMP）;模拟研究的连贯术语;编码模拟研究的指导;关键性能指标及其估计的关键讨论;结构化结果的表格和图形表示的指导;和新的图形演示。为了描述最近的实践，我们回顾了100篇来自医学统计第34卷的文章，其中至少包括一项模拟研究，并确定了需要改进的地方。
Simulation studies are computer experiments that involve creating data by pseudo-random sampling. A key strength of simulation studies is the ability to understand the behavior of statistical methods because some truth (usually some parameter/s of interest) is known from the process of generating the data. This allows us to consider properties of methods, such as bias. While widely used, simulation studies are often poorly designed, analyzed, and reported. This tutorial outlines the rationale for using simulation studies and offers guidance for design, execution, analysis, reporting, and presentation. In particular, this tutorial provides a structured approach for planning and reporting simulation studies, which involves defining aims, data-generating mechanisms, estimands, methods, and performance measures (ADEMP); coherent terminology for simulation studies; guidance on coding simulation studies; a critical discussion of key performance measures and their estimation; guidance on structuring tabular and graphical presentation of results; and new graphical presentations. With a view to describing recent practice, we review 100 articles taken from Volume34 of Statistics in Medicine, which included at least one simulation study and identify areas for improvement.