Generalizability theory is a modern and powerful framework for conducting reliability analyses. It is flexible to accommodate both random and fixed facets. However, there has been a relative scarcity in the practical literature on how to handle the fixed facet case. This article aims to provide practitioners a conceptual understanding and computational resources to deal with designs with a fixed facet in both univariate and multivariate generalizability theory settings. The analyses feature a real data set, which is available to readers along with the code to reproduce all analyses.