PhD studentship in Statistics at Maastricht University, The Netherlands.
Project: Efficient two-stage design of multilevel intervention studies:
more power for the same price
Job description
This research project, funded by a grant from the Netherlands Organisation for Scientific
Research (NWO), is about efficient design of intervention studies in psychology and
health sciences. Such studies concern the effects of behavioral treatments, such as
smoking prevention in primary school or a therapy for depression. The studies often have
a nested design (patients in health centers, pupils in schools, employees in companies)
with repeated outcome measurements. Sometimes they additionally have a factorial
design to study the combined effects of two treatments. This project is about optimal and
robust design of such studies, in particular about the best sample size at each level
(organisation, person, repeated measure), under cost and power constraints. Part of the
project is about efficiency gains by two-stage and multi-stage design, where interim
analysis after part of the data have been obtained, determines whether the study should be
continued or stopped.
The PhD student will primarily do research, follow courses according to his or her needs
(e.g. advanced statistics, computer programming, Dutch or English language), and do
some teaching at bachelor level (about 10% of the time). The research is applied
mathematical (analytical, numerical, simulation), not empirical. However, its theoretical
results will be illustrated with data from published intervention studies.
Requirements
A master degree in statistics, biometrics, econometrics, psychometrics, or a related field
with a solid training in statistics. Applicants are expected to be familiar with the general
linear model, some matrix algebra, and computer programming (e.g. in Matlab). Further
requirements are good (written and oral) communication skills in English, and an
authorization to work in the European Union.
Further information
This is a four year temporary contract. For further information on the conditions of
employment, the organisation in which the candidate will work, and the application
procedure, see www.academictransfer.com/6462 (vacancy number AT2010.197).
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