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, 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.

Conditions of employment

Temporary employment for 4 years.

Your salary would be € 2.042,– gross per month in the first year up to € 2.612,– gross per month in the fourth year according to the PhD-student salary scale.

Each year an evaluation will take place.

Contract type

Temporary

4 years

Organisation

Maastricht University

Maastricht University is renowned for its unique, innovative, problem-based learning system, which is characterized by a small-scale and student-oriented approach. Research at UM is characterized by a multidisciplinary and thematic approach, and is concentrated in research institutes and schools. Maastricht University has around 14,000 students and 3,500 employees. Reflecting the university’s strong international profile, a fair amount of both students and staff are from abroad. The university hosts 6 faculties: Faculty of Health, Medicine and Life Sciences, Faculty of Law, School of Business and Economics, Faculty of Humanities and Sciences, Faculty of Arts and Social Sciences, Faculty of Psychology and Neuroscience.

Department

The Department of Methodology & Statistics

The Department of Methodology & Statistics of Maastricht University, The Netherlands is a mix of scientific and supporting personnel from the Faculty of Health, Medicine and Life sciences and the Faculty of Psychology & Neuroscience. The present PhD vacancy is within this last faculty. The research of the department focuses on optimal design and analysis of studies in health sciences and psychology, based on mixed effects models. This research is embedded in the School for Public Health and Primary Care (CAPHRI) at Maastricht University, and the Dutch Interuniversity graduate school of Psychometrics and Sociometrics (IOPS). The department gives courses in methodology and statistics to bachelor, master and PhD students, and does statistical consultancy, in both faculties.

Additional information

For further information please contact dr. Gerard van Breukelen, 00 31 (0) 43 3884001/2274

<p>gerard.vbreukelen@stat.unimaas.nl (until 10 October 2010)

<p>gerard.vbreukelen@maastrichtuniversity.nl (from 10 October 2010)

Spesifications

Location: Maastricht6200 MDLimburg
Scientific fields: Health, Behaviour and Society, Statistics
Function types: PhD positions
Education: University Graduate
Hours: 32.0 – 38.0 hours per week
End procedure: 1 November 2010
Job number: AT2010.197