标题： 弥合方法论研究与统计实践之间的差距：迈向“转化模拟研究” 显示英文标题

标题： Bridging the Gap Between Methodological Research and Statistical Practice: Toward "Translational Simulation Research

摘要： 模拟是实证评估统计方法属性的有用工具，主要用于方法论研究中得出关于方法的一般结论。 此外，它们通常对应用统计学家也有用，他们可能依赖于已发表的模拟结果来选择适合其应用的统计方法。 然而，一方面，直接将已发表的模拟结果应用于实际环境通常具有挑战性，因为方法论研究中考虑的场景很少能与特定现实应用的特征足够接近，从而真正提供信息。 另一方面，应用统计学家可能由于时间限制和有限的编程技能，在构建自己的模拟或调整方法论研究以更好地反映其特定数据时遇到困难。 我们通过开发专用软件和模拟研究，采用一种翻译方法来弥合方法论研究与统计实践之间的差距，这应抽象掉运行模拟的编码密集部分，同时仍提供足够的参数选择灵活性以满足应用统计学家的需求。 我们使用两个实际例子来演示这种方法，说明翻译模拟的概念可以以不同的方式在实践中实现。 在第一个例子——具有有序终点的两组随机临床试验中的功效基于模拟评估中，我们讨论的解决方案是一个Shiny网络应用程序，为在此背景下运行信息丰富的模拟提供图形用户界面。 对于第二个例子——评估多变量回归中的测量误差影响，建议采用一种更省力的方法，包括提供用户友好、结构良好且模块化的分析代码。 显示英文摘要

摘要： Simulations are valuable tools for empirically evaluating the properties of statistical methods and are primarily employed in methodological research to draw general conclusions about methods. In addition, they can often be useful to applied statisticians, who may rely on published simulation results to select an appropriate statistical method for their application. However, on the one hand, applying published simulation results directly to practical settings is frequently challenging, as the scenarios considered in methodological studies rarely align closely enough with the characteristics of specific real-world applications to be truly informative. Applied statisticians, on the other hand, may struggle to construct their own simulations or to adapt methodological research to better reflect their specific data due to time constraints and limited programming expertise. We propose bridging this gap between methodological research and statistical practice through a translational approach by developing dedicated software along with simulation studies, which should abstract away the coding-intensive aspects of running simulations while still offering sufficient flexibility in parameter selection to meet the needs of applied statisticians. We demonstrate this approach using two practical examples, illustrating that the concept of translational simulation can be implemented in practice in different ways. In the first example - simulation-based evaluation of power in two-arm randomized clinical trials with an ordinal endpoint - the solution we discuss is a Shiny web application providing a graphical user interface for running informative simulations in this context. For the second example - assessing the impact of measurement error in multivariable regression - a less labor-intensive approach is suggested, involving the provision of user-friendly, well-structured, and modular analysis code.