Dear all,
Professor Donald Rubin will be giving a special lecture on methodological issues in the evaluation of a job-training programme - The lecture will take place 5.30-6.30pm, Tuesday 12 October at the British Academy in London, and will be followed by a reception.
Abstract: In recent years, job-training programmes have become increasingly important in many developed countries with rising unemployment. It is widely accepted that the best way to evaluate such programmes is to conduct randomized experiments. With these, among a group of people who indicate that they want job-training, some are randomly assigned to be offered the training and the others are denied it, at least initially. According to a well-defined protocol, outcomes such as employment statuses or wages for those who are employed are then measured for those who were offered the training and compared to the same outcomes for those who were not.
Despite the high cost of these experiments, their results can be difficult to interpret because of inevitable complications when doing experiments with humans. Three in particular are that some people do not comply with their assigned treatment, others drop out of the experiment before outcomes can be measured, and others who stay in the experiment are not employed, and thus their wages are not cleanly defined.
Statistical analyses of such data can lead to important policy decisions, and yet the analyses typically deal with only one or two of these complications, which may obfuscate subtle effects. An analysis that simultaneously deals with all three complications generally provides more accurate conclusions.
Venue
The British Academy, 10 Carlton House Terrace, London SW1Y 5AH
(http://www.britac.ac.uk/contact/map.cfm)
Registration is not required for this event. Seats will be allocated on arrival.
About the speaker:Professor Rubin is John L. Loeb Professor of Statistics at Harvard University. He has made, and continues to make, many important contributions to statistical methodology and its wider application. These include the Rubin Causal Model, propensity scores, and principal stratification, for the analysis of experiments and observational studies. All of these approaches are widely used in quantitative social science, the biomedical sciences, and beyond, and continue to underpin cutting edge research in the field of mathematical statistics. He was elected a Corresponding Fellow of the British Academy in 2009.
With best regards,
Hilary Browne
Technical and Business Manager
(Part-time: working days Tuesdays, Thursdays and Fridays)
Centre for Multilevel Modelling
University of Bristol
2 Priory Road
Bristol BS8 1TX
Tel: +44 (0)117 331 0847
Web: <http://www.cmm.bristol.ac.uk>
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