Exploratory structural equation (ESEM) has received increased attention in the methodological literature as a promising tool for evaluating latent variable measurement models. It overcomes many of the limitations attached to exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), while capitalizing on the benefits of each. Given that the recent introduction of ESEM in statistical software has made its use more accessible to applied researchers, we describe the differences between these three approaches to evaluating measurement models and provide an illustration of their differences through an applied example. Syntax for running these models is also provided that can be modified for application by others.