Computational modeling holds significant promise as a tool for improving how theory is developed, expressed, and used to inform empirical research and evaluation efforts. However, the knowledge and skillsets needed to build computational models are rarely developed in the training received by social and organizational scientists. The purpose of this manuscript is to provide an accessible introduction to and reference for building computational models to represent theory. We first discuss important principles and recommendations for “thinking about” theory and developing explanatory accounts in ways that facilitate translating their core assumptions, specifications, and ideas into a computational model. Next, we address some frequently asked questions related to building computational models that introduce several fundamental tasks/concepts involved in building models to represent theory and demonstrate how they can be implemented in the R programming language to produce executable model code. The accompanying supplemental materials describes additional considerations relevant to building and using computational models, provides multiple examples of complete computational model code written in R, and an interactive application offering guided practice on key model-building tasks/concepts in R.

中文翻译：

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你好世界！建立代表社会和组织理论的计算模型


计算模型作为改进理论开发、表达和使用方式为实证研究和评估工作提供信息的工具，具有重大前景。然而，社会和组织科学家接受的培训很少培养建立计算模型所需的知识和技能。本手稿的目的是为构建代表理论的计算模型提供易于理解的介绍和参考。我们首先讨论“思考”理论和开发解释性说明的重要原则和建议，以促进将其核心假设、规范和想法转化为计算模型。接下来，我们解决一些与构建计算模型相关的常见问题，介绍构建模型所涉及的几个基本任务/概念来表示理论，并演示如何在 R 编程语言中实现它们以生成可执行模型代码。随附的补充材料描述了与构建和使用计算模型相关的其他注意事项，提供了用 R 编写的完整计算模型代码的多个示例，以及提供 R 中关键模型构建任务/概念的指导实践的交互式应用程序。