The predictive validity of grade point average scores in a partial lottery medical school admission system

Med Educ. 2006 Oct;40(10):1012-9. doi: 10.1111/j.1365-2929.2006.02561.x.

Abstract

Purpose: To ascertain whether the grade point average (GPA) of school-leaving examinations is related to study success, career development and scientific performance. The problem of restriction of range was expected to be partially reduced due to the use of a national lottery system weighted in favour of students with higher GPAs.

Method: We studied the students (n = 398) admitted to the Faculty of Medicine, University of Groningen, the Netherlands in 1982 and 1983. Data concerning drop-out and study progress were derived from the student administration. Data about career development were obtained from annual interviews with graduates (n = 318) between 1993 and 2000. Literature searches yielded data concerning scientific performance. Multiple linear regression and logistic regression were used to analyse the data. The variables 'gender' and 'cohort' and their interaction were included in the analyses to account for variation in the general level of the dependent variable and the effect of GPA on the dependent variable.

Results: GPA scores had no effect on drop-out rate. High GPA scores were associated with significantly less time to graduation, more chance of a preferred placement for specialist training and higher scientific output. GPA was not related to income. Gender differences were found for study duration and scientific output. Women graduated earlier and published less.

Conclusion: The GPA of school-leaving examinations was found to be related to study success, career development and scientific performance. In this study the usual problem of restriction of range was shown to be absent. The weighted lottery procedure even resulted in an over-dispersion of candidates relative to the applicants. The resulting effect sizes were in agreement with those reported in other studies.

MeSH terms

  • Career Mobility*
  • Education, Premedical*
  • Educational Status
  • Predictive Value of Tests
  • Regression Analysis
  • School Admission Criteria*
  • Schools, Medical*