The purpose of this chapter is to discuss the conceptual, methodological, and statistical challenges in selecting appropriate peer institutions for comparative purposes. The authors' approach embraces a Western scientific tradition that physical things and phenomena can be "reduced into a set of key variables--identifiable parts--that make key…

Multilevel modeling (MLM), also referred to as hierarchical linear modeling (HLM) or mixed models, provides a powerful analytical framework through which to study colleges and universities and their impact on students. Due to the natural hierarchical structure of data obtained from students or faculty in colleges and universities, MLM offers many…

Compared to traditional classification methods, developing a peer group using the National Center for Educational Statistics (NCES) Integrated Postsecondary Education Data Systems (IPEDS) data allows institutions to add comparative dimensions, to update the peer group, and to track changes at peer institutions over time. Peer selection and…