Principal component analysis (PCA) and factor analysis (FA) are variable reduction techniques used to represent a set of observed variables in terms of a smaller number of variables. While PCA and FA are similar along several dimensions (e.g., extraction of common components/factors), researchers often fail to recognize that these techniques achieve different goals and can produce significantly different results. We conduct a comprehensive review of the use of PCA and FA in accounting research. We offer guidelines on programming PCA and FA in SAS/Stata and emphasize the importance of implementation techniques as well as the disclosure choices made when utilizing these methodologies. Furthermore, we present intuitive, practical examples highlighting the differences between the techniques and provide suggestions for researchers considering the use of these procedures. Finally, based on our review, we provide recommendations, observations, notes, and citations to the literature, regarding the implementation of PCA and FA in accounting.