There has been growing criticism of the established practice of automatically including control variables into analyses, especially with survey studies. Several authors have explained the pitfalls of improper use and have provided some best practice advice. I build upon this foundation in suggesting a programmatic approach to the use of control variables that can provide evidence to support or refute feasible explanations for why two or more variables are related. The hierarchical iterative control (HIC) approach begins by establishing a connection between two or more variables and then hierarchically adds control variables to rule in or out their possible influence. The HIC approach involves conducting a series of studies to iteratively test relationships among target variables, utilizing a variety of control variable strategies involving multiple methods. A 7-step programmatic approach is described beginning with development of the research question and background literature review and then conducting empirical tests in a hierarchical (within a study) and iterative (across studies) manner.

对自动将控制变量纳入分析的既定做法提出了越来越多的批评，尤其是在调查研究中。几位作者解释了不当使用的陷阱，并提供了一些最佳实践建议。我在此基础上建议使用控制变量的程序化方法，该方法可以提供证据来支持或反驳为什么两个或多个变量相关的可行解释。分层迭代控制 (HIC) 方法首先在两个或多个变量之间建立连接，然后分层添加控制变量以排除或排除它们可能的影响。HIC 方法涉及进行一系列研究以迭代测试目标变量之间的关系，利用涉及多种方法的各种控制变量策略。描述了一个 7 步程序化方法，从研究问题的发展和背景文献回顾开始，然后以分层（研究内）和迭代（跨研究）方式进行实证测试。