In this course, participants will delve into the intricacies of data analysis by utilizing structural equation modeling (SEM) with the R programming language, specifically employing the lavaan package. SEM offers a comprehensive approach to understanding the interconnections and structure of data, enabling the creation of predictive models for future events. Throughout the course, participants will gain proficiency in handling latent and manifest variables, constructing measurement models, evaluating the accuracy of these models, and rectifying inadequately fitting models. Additionally, participants will have the opportunity to explore renowned SEM datasets, including the Holzinger and Swineford (1939) and Bollen (1989) datasets. Furthermore, a multi-factor model case study utilizing the Wechsler Adult Intelligence Scale will be undertaken. By the conclusion of this course, participants will possess the skills necessary to conduct in-depth analyses of their own data, facilitating a comprehensive understanding of its underlying structure.