This is one of a series of monographs on research design and analysis. The purpose of this article is to describe a set of statistical procedures or techniques used to develop and test structural models that characterize the relationships and interrelationships between a group of concepts and variables. These procedures include multiple regression, exploratory and confirmatory factor analysis, path analysis, and structural equation modeling. The article describes the purpose of each of these procedures and how they relate to and build on one another. It also covers the different types of variables examined, including the distinction between endogenous, exogenous, and mediating variables, along with the distinction between measured and unmeasured (or latent) variables. Each procedure results in a set of statistical estimates, and the article presents the interpretation of these estimates, including regression coefficients (standardized and unstandardized), path coefficients, factor loadings, and coefficients of determination (or R² values). The article presents examples of how each procedure has been used in practice, along with additional resources for readers who wish to learn more.