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Conducting Simulation Studies in the R Programming Environment

机译:在R编程环境中进行仿真研究

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摘要

Simulation studies allow researchers to answer specific questions about data analysis, statistical power, and best-practices for obtaining accurate results in empirical research. Despite the benefits that simulation research can provide, many researchers are unfamiliar with available tools for conducting their own simulation studies. The use of simulation studies need not be restricted to researchers with advanced skills in statistics and computer programming, and such methods can be implemented by researchers with a variety of abilities and interests. The present paper provides an introduction to methods used for running simulation studies using the R statistical programming environment and is written for individuals with minimal experience running simulation studies or using R. The paper describes the rationale and benefits of using simulations and introduces R functions relevant for many simulation studies. Three examples illustrate different applications for simulation studies, including (a) the use of simulations to answer a novel question about statistical analysis, (b) the use of simulations to estimate statistical power, and (c) the use of simulations to obtain confidence intervals of parameter estimates through bootstrapping. Results and fully annotated syntax from these examples are provided.
机译:通过仿真研究,研究人员可以回答有关数据分析,统计功效以及在实证研究中获得准确结果的最佳实践的特定问题。尽管模拟研究可以提供好处,但许多研究人员并不熟悉进行自己的模拟研究的可用工具。模拟研究的使用不必仅限于具有统计学和计算机编程高级技能的研究人员,此类方法可以由具有各种能力和兴趣的研究人员实施。本文提供了使用R统计编程环境进行模拟研究的方法的介绍,并且是针对那些对模拟研究或R使用经验很少的个人编写的。本文介绍了使用模拟的原理和好处,并介绍了与R相关的R函数。许多模拟研究。三个示例说明了模拟研究的不同应用,包括(a)使用模拟回答关于统计分析的新问题;(b)使用模拟估计统计功效;以及(c)使用模拟获得置信区间通过引导进行参数估计。提供了这些示例的结果和完整注释的语法。

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