This study empirically explores the comparability of traditional survey-based retention research methodology with an alternative approach that relies on data commonly available in institutional student databases. Drawing on Tinto's [Tinto, V. (1993). "Leaving College: Rethinking the Causes and Cures of Student Attrition" (2nd Ed.), The University of Chicago Press, Chicago.] theory of student integration, this project utilizes an information-theoretic approach [Burnham, K. P., and Anderson, D. R. (2002). "Model Selection and Inference: A Practical Information-theoretical Approach" (2nd ed.), Springer-Verlag, New York, NY.], in which a set of candidate models was developed using institutional integration survey variables and variables drawn from institutional student databases. An information-theoretic approach to selecting the most parsimonious logistic regression model revealed that institutional database variables out-perform the institutional integration survey scales developed by Pascarella and Terenzini [Pascarella, E. T., and Terenzini, P. T. (1980). "Journal of Higher Education" 51(1): 60-75.] in predicting 1-year retention. This empirical support for the use of institutional database variables is valuable in conducting institution-specific retention research under constrained resources.