Effects of in-class variation and student rank on the probability of withdrawal: cross-section and time-series analysis for UK university students

From individual level longitudinal data for two entire cohorts of medical students in UK universities, we use multilevel models to analyse the probability that an individual student will drop out of medical school. We find that academic preparedness-both in terms of previous subjects studied and...

From individual-level data for nine entire cohorts of undergraduate students in UK universities, we estimate the probability that an individual will drop out of university during their first-year. We examine the 1984-85 to 1992-93 cohorts of students enrolling full-time for a three or four-year...

From individual-level longitudinal data for two entire cohorts of medical students in UK universities, we analyse the probability that an individual student will ‘drop out’ of medical school prior to the successful completion of their studies. We examine the cohort of students enrolling for...

We exploit a rich administrative panel data-set for cohorts of Economics students at a UK university in order to identify causal effects of class absence on student performance. We exploit the panel properties of the data to control for unobserved heterogeneity across students and hence for...

In the context of the UK Government’s ambitious programme of medical school expansion, it is important to have an understanding of how the medical school admissions process works, and with what effects. The issue is also relevant for the Schwartz Review (2004) into higher education admissions....

We analyse a rich dataset of Economics students at a UK university to identify causal effects of class absence on student performance, exploiting the random assignment of students and information on students’ class timetables to avoid selection problems. We use panel properties of the data to...

Objectives To assess the extent to which various factors influence the probability that an individual medical student will drop out of medical school during their first year of study, focusing on the influence both of prior qualifications, such as A-level subjects taken and scores attained, and...

We exploit a rich administrative panel data-set for cohorts of Economics students at a UK university in order to identify causal effects of class absence on student performance. We utilise the panel properties of the data to control for unobserved heterogeneity across students and hence for...