Who Are Our Peers? Using k-Prototypes Clustering to Construct Institutional Peer Groups

This article presents a reproducible public-data methodology for constructing institutional peer groups in higher education. Using Integrated Postsecondary Education Data System (IPEDS) data, we develop a two-stage k-prototypes clustering workflow that accommodates both numerical and categorical institutional features. The first stage identifies a broad institutional comparison set across all IPEDS institutions, while the second stage reclusters institutions within the focal institution’s global cluster to identify a more focused local peer group. Using St. Bonaventure University as a case example, the procedure identified a global comparison cluster of 1,132 institutions and a local peer cluster of 247 institutions. We further use a random forest classifier and shallow decision-tree surrogate to summarize the institutional characteristics that distinguish the resulting local clusters. The framework provides a transparent and adaptable approach for institutional peer-group construction using publicly available data and open-source analytical tools.