Transforming variables before analysis or applying a transformation as a part of a generalized linear model are common practices in organizational research. Several methodological articles addressing the topic, either directly or indirectly, have been published in the recent past. In this article, we point out a few misconceptions about transformations and propose a set of eight simple guidelines for addressing them. Our main argument is that transformations should not be chosen based on the nature or distribution of the individual variables but based on the functional form of the relationship between two or more variables that is expected from theory or discovered empirically. Building on a systematic review of six leading management journals, we point to several ways the specification and interpretation of nonlinear models can be improved.

在分析之前对变量进行转换或将转换作为广义线性模型的一部分进行应用是组织研究中的常见做法。最近，已经发表了一些直接或间接涉及该主题的方法论文章。在本文中，我们指出了一些有关转换的误解，并提出了一套解决这些转换的八种简单指南。我们的主要论点是，不应基于单个变量的性质或分布来选择转换，而应基于理论上预期或凭经验发现的两个或多个变量之间关系的函数形式。在对六种领先管理期刊的系统评价的基础上，我们指出了可以改进非线性模型的规范和解释的几种方法。