Abstract
Exploratory Factor Analysis (EFA) is a widely used approach for exploring latent traits. The EFA literature contains many inconsistencies regarding appropriate sample sizes, remedies for violation of assumptions, and the use of rotational methods. Given that EFA is an iterative process, which involves varied decision-making, the objective of the current paper is to highlight the use of modernized methods using a heuristic approach for performing robust EFA to achieve optimal results. An example implementing these methods is presented using free online software (FACTOR). The paper concludes with seven recommendations for achieving well-defined factor solutions.