Research in Higher Education

, Volume 40, Issue 3, pp 355–371 | Cite as


  • Paul A. Murtaugh
  • Leslie D. Burns
  • Jill Schuster


Survival analysis was used to model theretention of 8,867 undergraduate students at OregonState University between 1991 and 1996. Attrition wasfound to increase with age, and decrease with increasing high school GPA and first-quarter GPA.Non-residents had higher attrition rates than didresident and international students, and students takingthe Freshman Orientation Course appeared to be atreduced risk of dropping out. Statistically significantassociations of retention with ethnicity/race andcollege at first enrollment were also noted. Aproportional hazards regression model was developed topredict a student's probability of leaving school basedon these demographic and academic variables. Theseanalyses are helping to guide the university's effortsto improve retention through marketing, recruitment, and the development of orientation and otherprograms.


Regression Model High School Survival Analysis Undergraduate Student Education Research 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Anonymous (1997). Freshman-to-s ophomore persistence rates, 1983-1997. Postsecondary Education OPPORTUNITY, Number 60, pp. 1-7. The Mortenson Research Seminar on Public Policy Analysis of Opportunity for Postsecondary Education, Iowa City, Iowa.Google Scholar
  2. Astin, A. W. (1993). What Matters in College: Four Critical Years Revisited. San Francisco: Jossey-Bass.Google Scholar
  3. Avakian, A. N., MacKinney, A. C., and Allen, G. R. (1982). Race and sex differences in student retention at an urban university. College and University57: 160-165.Google Scholar
  4. Bedford, M. H., and Durkee, P. E. (1989). Retention: Some more ideas. NASPA Journal27: 168-171.Google Scholar
  5. Boudreau, C. A., and Kromrey, J. D. (1994). A longitudinal study of the retention and academic performance of participants in freshmen orientation course. Journal of College Student Development35: 444-449.Google Scholar
  6. Breslow, N. E. (1974). Covariance analysis of censored survival data. Biometrics30: 89-99.Google Scholar
  7. Cabrera, A. F., Nora, A., and Casta Äneda, M. B. 1993. College persistence: Structural equations modeling test of an integrated model of student retention. Journal of Higher Education64: 123-139.Google Scholar
  8. Collett, D. (1994). Modelling Survival Data in Medical Research. New York: Chapman and Hall.Google Scholar
  9. Cox, D. R. (1972). Regression models and life tables (with discussion). Journal of the Royal Statistical Society B34: 187-220.Google Scholar
  10. Dey, E. L., and Astin, A. W. (1993). Statistical alternatives for studying college student retention: A comparative analysis of logit, probit, and linear regression. Research in Higher Education34: 569-581.Google Scholar
  11. Dodd, J. M., Garcia, F. M., and Nelson, J. R. (1995). American Indian student retention. NASPA Journal33(1): 72-78.Google Scholar
  12. Dougherty, R. C., Bowen, C. W., Berger, T., Rees, W., Mellon, E. K., and Pulliam, E. (1995). Cooperative learning and enhanced communication: Effects on student performance, retention, and attitudes in general chemistry. Journal of Chemical Education72(9): 793-797.Google Scholar
  13. Glass, J. C., and Garrett, M. S. (1995). Student participation in a college orientation course, retention, and grade point average. Community College Journal of Research and Practice19: 117-132.Google Scholar
  14. Harrell, F. E., Jr., Lee, K. L., and Mark, D. B. (1996). Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Statistics in Medicine15: 361-387.Google Scholar
  15. Heiberger, R. M. (1993). Predicting next year' s enrollm ent: Survival analysis of university student enrollm ent histories. Proceedings of the American Statistical Association, Social Statistical Section, pp. 143-148.Google Scholar
  16. Hyman, R. E. (1995). Creating campus partnerships for student success. College and University71: 2-8.Google Scholar
  17. Johnson, R. (1996). The adult student: Motivation and retention. The American Music Teacher46(2): 16-18, 60-61.Google Scholar
  18. Kalbfleisch, J. D., and Prentice, R. L. (1980). The Statistical Analysis of Failure Time Data. New York: Wiley.Google Scholar
  19. Kaplan, E. L., and Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association53: 457-481.Google Scholar
  20. Lawless, J. F. (1982). Statistical Models and Methods for Lifetime Data. New York: Wiley.Google Scholar
  21. Lee, E. T. (1992). Statistical Methods for Survival Data Analysis. New York: Wiley.Google Scholar
  22. Moore, R., and Miller, I. (1996). How the use of multimedia affects student retention and learning. Journal of College Science Teaching25(4): 289-293.Google Scholar
  23. Naretto, J. A. (1995). Adult student retention: The influence of internal and external communities. NASPA Journal32: 90-97.Google Scholar
  24. Person, D. R., and Christensen, M. C. (1996). Understanding black student culture and black student retention. NASPA Journal34(1): 47-56.Google Scholar
  25. Peto, R., and Peto, J. (1972). Asymptotically efficient rank invariant procedures. Journal of the Royal Statistical Society, Series A135: 185-207.Google Scholar
  26. Reyes, N. (1997). Holding on to what they' ve got. Black Issues in Higher Education13(26): 36-40.Google Scholar
  27. Statistical Sciences Inc. (1993). S-Plus Statistical Software, User's ManualVersion 3.2. Seattle: Statistical Sciences Inc.Google Scholar
  28. Tinto, V. (1993). Leaving College: Rethinking the Causes and Cures of Student Attrition. Chicago: The University of Chicago Press.Google Scholar
  29. Volkwein, J. F., and Lorang, W. G. (1996). Characteristics of extenders: Full-time students who take light credit loads and graduate in more than four years. Research in Higher Education37: 43-68.Google Scholar

Copyright information

© Human Sciences Press, Inc. 1999

Authors and Affiliations

  • Paul A. Murtaugh
  • Leslie D. Burns
  • Jill Schuster

There are no affiliations available

Personalised recommendations