Missing Data

''To prevent is better than to cure.''

Even in well designed and conducted epidemiological studies, data will be missing. This may include missing observations of the exposure and under study, confounders, or the outcome.

Possible mechanisms for data being missing will be discussed, as well as their potential impact in terms of bias. Focus will be on methods to handle missing data. Examples and exercises will come from various epidemiological studies, including diagnostic, prognostic, etiologic, and therapeutic studies.


Start date(s): 
2 June 2020
Time investment: 
Four full working days
University Medical Center Utrecht
Faculty of Medicine
Fee: This fee is exempt from VAT
€ 830

At the end of the course, you are able to:

  • Explain different mechanisms giving rise to missing data
  • Recognize missing data as a potential source of bias in epidemiologic research
  • Describe key assumptions of methods to handle missing data
  • Apply imputation methods to deal with missing data


Please contact our Educational Office:
​088 75 69710