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TU Berlin

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4. BerlinHECOR Workshop (2016)

Das Gesundheitsökonomische Zentrum Berlin (BerlinHECOR) veranstaltet vom 12.-14. September 2016 einen Methodenkurs zum Thema "Multiple Imputation in Practice"

Die Teilnahme ist kostenlos. Bitte melden Sie sich bis zum 19. August 2016 unter der E-Mail-Adresse verena.vogt[at]tu-berlin.de an (erforderliche Angaben sind Name, Institution, Kontaktdaten, Fachrichtung und akademischer Grad). Aufgrund der begrenzten Teilnehmerzahl wird eine möglichst frühe Anmeldung empfohlen. Kurssprache ist Englisch.

Ansprechpartnerin für weitere Fragen ist Verena Vogt.

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Multiple Imputation in Practice


Most researchers in the medical, social and behavioural sciences have encountered the problem of missing data: It seriously complicates the statistical analysis of data, and simply ignoring it is not a good strategy. A general and statistically valid technique to analyze incomplete data is multiple imputation, which is rapidly becoming the standard in medical, social and behavioural science research.

This 3-day course will explain a modern and flexible imputation technique that is able to obtain valid inference, whilst preserving important features in the data. The aim of this course is to enhance participants’ knowledge in imputation methodology, and to provide a flexible solution to their incomplete data problems using R. The course will explain the principles of missing data theory, outline a step-by-step approach toward creating high quality imputations, and provide guidelines how the results can be reported. The course will use the authors' MICE package in R, and explain how to bridge to mainstream analysis software such as SPSS and Mplus. The lectures will follow the book “Flexible Imputation of Missing Data” by Stef van Buuren (Chapman & Hall, 2012). This book has to be purchased in advance.

Target audience

This course is relevant for applied researchers or statistical researchers that would like to get acquainted with the theory and practice of multiple imputation. Participants should have basic understanding of statistical techniques (such as analysis of variance and (non)linear regression) and the concept of statistical inference. No prior programming experience with R is required.


Familiarity to basic statistical concepts and techniques - see target audience.

Specific details

Lecturers: Stef van Buuren (Netherlands Organization for Applied Scientific Research (TNO) and Utrecht University, NL), Gerko Vink (Utrecht University, NL, Columbia University, NY, USA)

Time: 09.00 – 17.00 hrs.




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