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…

This study provides a multilens examination of the diversity of full-time faculty in the United States across 11 institutional types derived from Carnegie classifications, by the intersection of race/ethnicity, citizenship, and gender and to make comparisons across time. Whereas few other studies have assessed faculty diversity for the for-profit…

Research studies show that high school experiences, engagement, and academic achievement, as well as entering expectations and attitudes, are important predictors of student success. Therefore, to better understand first-year student engagement, it makes sense to consider the backgrounds and precollege characteristics of entering college students.…

Data mining of IPEDS data is used to develop models that calculate predicted graduation rates for two- and four-year institutions. (Contains 7 tables and 5 figures.)

Focusing on student retention and time to degree completion, this study illustrates how institutional researchers may benefit from the power of predictive analyses associated with data-mining tools. The following are appended: (1) Predictors; and (2) Variable Definitions. (Contains 5 figures.)