Latent structure is a conceptual framework and area of statistical modeling focused on identifying and characterizing unobservable, underlying variables or dimensions that explain the relationships and patterns observed in manifest (directly measured) data. It investigates the hidden organization, groupings, or continuous factors that give rise to observed correlations or associations among variables, offering a more parsimonious and fundamental understanding of complex phenomena across various disciplines.