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Personal information

Martijn W Heymans is working as an assistant professor at the department of Epidemiology and Biostatistics of the VU University Medical Center, Amsterdam and the department of Methodology and Applied Biostatistics of the Faculty of Earth and Life Sciences, VU University Amsterdam. His work consists of statistical consultancy (http://www.vumc.nl/afdelingen/EB/medewerkers/sectiebiostatistiek/2225443/), supervising PhD projects on several methodological and clinical topics as clinical prediction rules and missing data (see under Projects) and lecturing courses in epidemiology and biostatistics for the Master's Programme in Epidemiology (www.epidm.nl) and for the Bachelor and pre-master's programmes Health Sciences, Biomedical science and Health and Life Sciences.
 
Guidelines for Researchers
* Development of Prognostic and Clinical prediction models
 * Missing data
 
Main research topics
* Development and methodology of clinical prediction models.
* Regression Modeling and Longitudinal data analysis.
* Systematic Reviews of Prognosis and Prediction research.
* Missing data.
 
Software
* R.
* SAS.
* Stata.
* SPSS.
 
Courses
* Epidemiology (Epidm programme VUmc)
  - Clinical prediction models:
http://www.epidm.nl/cursussen/cursus.asp?d=41#Cursus+Klinische+predictiemodellen
 
  - Introduction in Biostatistics and Clinical Epidemiology:
http://www.epidm.nl/cursussen/cursus.aspid=29#Cursus+Inleiding+biostatistiek+en+klinische+epidemiologie
 
A couse on Missing data will start in 2013 !
 
* Bachelor's and Master's programme VU University,
  Biomedical Sciences, Health and Life Sciences and Health Sciences.
- Courses on Methodology, Epidemiology and Biostatistics.  
 
Background
To become experienced in medical and epidemiological research methodology he completed the studies Physiotherapy and Human Movement Sciences, a PhD thesis on Cost-effectiveness at the EMGO+ Institute for Health and Care Research, VU medical center, a post-doc period working on the development and validation of clinical prediction models and missing data and the Post graduate Epidemiology Programme. During his post-doc period he worked for 3 months at the University of Melbourne, Faculty of Medicine, Dentistry and Health Sciences, Australia. He followed workshops and courses of prediction and regression modeling, missing data, longitudinal data analysis of FE Harrell Jr, P Allison, E Lesaffre, G Molenberghs & G Verbeke, EW Steyerberg, P Royston & W Sauerbrei and JWR Twisk.
 
Some important papers
 
Vergouw D, Heymans MW, Peat GM, Kuijpers T, Croft PR, de Vet HC, van der Horst HE, van der Windt DA. The search for stable prognostic models in multiple imputed data sets. BMC Med Res Methodol. 2010;10(1):81.
 
Heymans MW, van Buuren S, Knol DL, Anema JR, van Mechelen W, de Vet HC. The prognosis of chronic low back pain is determined by changes in pain and disability in the initial period. Spine J. 2010 Jul 7. [Epub ahead of print]
 
Schellingerhout JM, Heymans MW, de Vet HC, Koes BW, Verhagen AP. Categorizing continuous variables resulted in different predictors in a prognostic model for nonspecific neck pain. J Clin Epidemiol 2009;62(8):868-74.
 
Heymans MW, Anema JR, van Buuren S, Knol DL, van Mechelen W, de Vet HC.
Return to work in a cohort of low back pain patients: development and validation of a clinical prediction rule. J Occup Rehabil. 2009;19(2):155-65.
 
Heymans MW, van Buuren S, Knol DL, van Mechelen W, de Vet HC. Variable selection under multiple imputation using the bootstrap in a prognostic study.
BMC Med Res Methodol. 2007 Jul 13;7:33.
 
See for more publications
 
International
http://www.ncbi.nlm.nih.gov/pubmed?term=heymans%20mw
 
National
http://www.emgo.nl/team/197/martijnheymans/publications/