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From individual level data for an entire cohort of undergraduate students in the`old' universities in the UK, we use a binomial probit model to estimate the probability that an individual will`drop out' of university before the completion of their degree course. We examine the cohort of students enrolling full time for a 3-or 4-year degree in the academic year 1989±1990. We ®nd evidence to support both the hypothesis that the completion of courses by students is in¯uenced by the extent of prior academic preparedness and the hypothesis that social integration at university is important. We also ®nd an in¯uence of unemployment in the county of prior residence, especially for poorer male students. Finally, we draw conclusions regarding the public policy of constructing university performance indicators in this area.

This article presents a formal explanation of the forecast combination puzzle, that simple combinations of point forecasts are repeatedly found to outperform sophisticated weighted combinations in empirical applications. The explanation lies in the effect of finite-sample error in estimating the combining weights. A small Monte Carlo study and a reappraisal of an empirical study by Stock and Watson ["Federal Reserve Bank of Richmond Economic Quarterly" (2003) Vol. 89/3, pp. 71-90] support this explanation. The Monte Carlo evidence, together with a large-sample approximation to the variance of the combining weight, also supports the popular recommendation to ignore forecast error covariances in estimating the weight. Copyright (c) Blackwell Publishing Ltd and the Department of Economics, University of Oxford, 2009.

The UK government is introducing new sets of indicators designed to measure the performance of universities. A ®rst wave of indicators was published in December 1999. A performance indicator based on graduate employment outcomes will follow. This paper proposes a method for developing employment-related performance indicators based on the analysis of data on the ®rst destinations of a full cohort of leavers from pre-1992 universities in the United Kingdom. We analyse the determinants of graduate ®rst destinations and suggest a method for the construction of university performance indicators. We also discuss limitations of league tables based on university performance indicators.

Policies aimed at increasing the size of the medical student intake in the UK and of widening access to students from non-traditional backgrounds should be informed by evidence that student dropout probabilities are sensitive to measures of A-level attainment, such as subject studied and scores achieved. If traditional entry requirements or standards are relaxed, then this is likely to have detrimental effects on medical schools' retention rates unless accompanied by appropriate measures such as focussed student support.

The efficiency of stem cell transplantation is limited by low cell retention. Intracoronary (IC) delivery is convenient and widely used but exhibits particularly low cell retention rates. We sought to improve IC cell retention by magnetic targeting. Rat cardiosphere-derived cells labeled with iron microspheres were injected into the left ventricular cavity of syngeneic rats during brief aortic clamping. Placement of a 1.3 Tesla magnet ~1 cm above the heart during and after cell injection enhanced cell retention at 24 h by 5.2–6.4-fold when 1, 3, or 5 × 105 cells were infused, without elevation of serum troponin I (sTnI) levels. Higher cell doses (1 or 2 × 106 cells) did raise sTnI levels, due to microvascular obstruction; in this range, magnetic enhancement did not improve cell retention. To assess efficacy, 5 × 105 iron-labeled, GFP-expressing cells were infused into rat hearts after 45 min ischemia/20 min reperfusion of the left anterior coronary artery, with and without a superimposed magnet. By quantitative PCR and optical imaging, magnetic targeting increased cardiac retention of transplanted cells at 24 h, and decreased migration into the lungs. The enhanced cell engraftment persisted for at least 3 weeks, at which time left ventricular remodeling was attenuated, and therapeutic benefit (ejection fraction) was higher, in the magnetic targeting group. Histology revealed more GFP+ cardiomyocytes, Ki67+ cardiomyocytes and GFP−/ckit+ cells, and fewer TUNEL+ cells, in hearts from the magnetic targeting group. In a rat model of ischemia/reperfusion injury, magnetically enhanced intracoronary cell delivery is safe and improves cell therapy outcomes.

BACKGROUNDIn the context of changing admissions criteria and an expanding medical school intake in the UK, we analyse the determinants of the medical school dropout probability. AIMSTo analyse the determinants of the probability that a student will drop out of medical school during their first year. To compare the results of this analysis over time. METHODLogistic regression analysis for the six intake cohorts of 1990-92 and 1998-2000. Between 1990Between -92 and 1998Between -2000, there was a substantial increase both in the size of the entry cohort and in the proportion of students dropping out of medical school. A logit model for the 1990-92 and the 1998-2000 cohorts reveals that the probability of dropping out depends on both the medical school attended and the personal characteristics of the students, including academic preparedness. Almost none of the increase in the dropout rate between the two cohorts can be explained by changes in observable characteristics of the students over this period. Instead, most of the increase in the dropout rate is associated with changes at the level of the institution and in unobserved student characteristics. RESULTS CONCLUSIONSUniversity effects, rather than changes in observed student characteristics, explain most of the increased dropout rate over the time period considered. Candidate explanations behind these effects include: less effective admissions policies; changing curricula, greater costs of attending 3 medical school and a growing mismatch between student and school characteristics. Testing between these competing hypotheses is left for future work. KEYWORDS OVERVIEW What is already known on this subjectRecent years have seen increases in the number of students entering UK medical schools and in the proportion dropping out. What this study addsFor the 1990-92 and 1998-2000 cohorts we find the probability of dropping out of medical school is lower for students (i) with better prior qualifications, (ii) with a parent who is a doctor, (iii) living on campus. Suggestions for further researchDespite the richness of our data, we find the increase in the dropout rate is mostly explained by changes in unobserved characteristics of students and medical schools. Future work should consider the influence of: admissions policies; changing curricula; social integration, and medical school fees. 5 INTRODUCTIONIn earlier work published in this Journal we investigated the factors affecting the probability of dropping out in the first year of medical school for the full populations of UK medical students over the period 1980 to 1992. 1 However, since 1992 many changes have taken place which are likely to have impacted on dropout probabilities, raising the issue of the extent to which results for earlier cohorts are informative for more recent cohorts. For recent cohorts of students the subject background at A-level is substantially more diverse compared to earlier. Similarly, there have been important curriculum and pedagogical changes Given all these changes, an analysis of ...

Abstract.From individual-level longitudinal data for two entire cohorts of medical students in UK universities, we use multi-level 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 levels of attainment therein -is the major influence on medical student withdrawal. Additionally, males and more mature students are more likely to withdraw than females or younger students, respectively. We find evidence that the factors influencing the decision to transfer course differ from those affecting the decision to drop out for other reasons. 1 IntroductionThe issue of the determinants of medical student dropout probabilities is important and topical in both the UK and beyond for a variety of reasons. First, there is serious and growing concern in the UK and elsewhere regarding a shortage in the domestic supply of medical doctors. The Third Report of the UK's Medical Workforce Standing Advisory Committee (MWSAC, 1997) observes that there will be a deficit of doctors in Europe early in this century (MWSAC, 1997. p. 30). This has led to Government-supported enquiries into the causes and potential cures for this problem. The most obvious policy initiative is to train more doctors. The MWSAC (1997) report concluded that a substantial increase in medical school intake was required to meet the future workforce needs of the UK National HealthService. In response, the Government allocated 1,129 new medical places, in a three-stage process commencing in 1999. The subsequent NHS Plan 2000 announced the Government's target of a further 1,000 medical places, with the expectation that the majority of the additional student intake will be in place by 2006. These changes imply that the total medical school intake will have almost doubled over a 10-year period from 1997. As has been highlighted in policy discussions (MWSAC, 1997), an expansion of medical student numbers begs questions regarding both student quality and student retention. This paper attempts to inform our understanding of the latter issue.A second reason for examining medical student dropout behaviour relates to the UK debate on the desirability of 'widening' access into higher education, in general, and into medical schools in particular. There has been a lively and high-profile debate in the UK concerning the extent of accessibility of medical schools to students regardless of their social or school background (see McManus (1998) and the related discussion). This has led to explicit recommendations to broaden access to undergraduate medical education (Angel and Johnson, 2000). Predicting the likely impact of such policies on retention and progression is 2 clearly an important issue. A third reason for analysing medical student withdrawal is related to the debate concerning the extent to which previous educational qualifications affect medical student performance and progression (see, for example, McManus et al., 1999).Additionally, Arulampalam, et...