This study applies a Bayesian latent variable analysis to the task of determining rankings of universities in the UK and US, on the basis of a set of quality-related measures. It estimates the degree of uncertainty in the rankings and permits the assessment of statistically significant differences across universities. It also provides a methodology for determining the weighting of various measures that is based on the patterns embedded in the data and compares the latent variable rankings with traditional weight-and-sum rankings. Overall, the methodology contributes to a better understanding of ranking efforts and illustrates the need for caution in interpreting distinctions published in traditional ranking systems.
This report is part of the RAND Corporation External publication series. Many RAND studies are published in peer-reviewed scholarly journals, as chapters in commercial books, or as documents published by other organizations.
Our mission to help improve policy and decisionmaking through research and analysis is enabled through our core values of quality and objectivity and our unwavering commitment to the highest level of integrity and ethical behavior. To help ensure our research and analysis are rigorous, objective, and nonpartisan, we subject our research publications to a robust and exacting quality-assurance process; avoid both the appearance and reality of financial and other conflicts of interest through staff training, project screening, and a policy of mandatory disclosure; and pursue transparency in our research engagements through our commitment to the open publication of our research findings and recommendations, disclosure of the source of funding of published research, and policies to ensure intellectual independence. For more information, visit www.rand.org/about/principles.
The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.