Multiple imputation techniques for working with missing data
Provider: Faculty of Health and Medical Sciences

Activity no.: 3336-19-00-00 
Enrollment deadline: 26/08/2019
Date and time16.09.2019, at: 08:00 - 17.09.2019, at: 15:00
Regular seats50
Course fee960.00 kr.
LecturersClaus Thorn Ekstrøm
ECTS credits1.40
Contact personSusanne Kragskov Laupstad    E-mail address:
Enrolment Handling/Course OrganiserPhD administration     E-mail address:

Aim and content
This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH. Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrolment deadline, available seats will be allocated to the waiting list.

The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at graduate schools in the other Nordic countries. All other participants must pay the course fee.

Learning objectives

Missing data is a common problem in many studies and is particularly prominent in large-scale studies and/or in studies involving repeated measurements over time. This course covers the general statistical techniques and methods based on multiple imputation using fully conditional model specification that are suitable for analyzing and obtaining unbiased results even missing data are a problem.

The course will contain equal parts theory and applications and consists of two full days of teaching and computer lab exercises. It is the intention that the participants will have a thorough understanding of the missing data mechanisms, their impact on the analyses, and how and when to use multiple imputation to alleviate the problems. Similarly, the students should be able to apply these methods practice after having followed the course. This course is aimed at health researchers with previous knowledge of statistics and the computer language R who need of an overview about appropriate analytical methods and discussions with statisticians to be able to solve their problem.

A student who has met the objectives of the course will be able to:

a. Analyze data to obtain unbiased results using fully conditional model specifications to be able to draw valid conclusions based on data containing missing observations.

b. Understand the advantages/disadvantages of the methods presented and be able to discuss potential pitfalls from using these methods, and when they are relevant.


Introduction to missing data problems and missing data mechanisms.
- Multiple imputations techniques and Rubin’s rules
- Advantages with fully conditional specifications
- Passive vs. active imputation
- Missing outcomes vs. missing predictors
- Using the smcfcs R package for multiple imputation analysis
- Pitfalls

The course is tailored for Ph.D.-students in health sciences who already have taken the Ph.D.-course “Basic Statistics for Health Researchers” or have a similar knowledge about statistics, and who wish to have more knowledge about the statistical methods underlying the approaches presented in the course.

A basic knowledge of statistics and previous experience with the software program R is expected. However, little or no previous exposure to the topics covered is expected.

Relevance to graduate programmes
The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH:

All Graduate Programmes


The course will consist of two full days with lectures before lunch and hands-on computer exercises after lunch each day.

Course director
Claus Thorn Ekstrøm, Professor, Section of Biostatistics, Department of Public Health, University of Copenhagen

Professor Jonathan Bartlett, University of Bath

Course secretary
Susanne Kragskov Laupstad

Monday 16 September and Tuesday 17 September 2019, both days 8-15.

Course location
The course takes place at the Center for Health and Society (Center for Sundhed og Samfund, at the former Kommunehospitalet, Øster Farimagsgade 5), at the University of Copenhagen

Please register before 19 August 2019

Admission to PhD students from Danish universities will be allocated on a first-come, first-served basis and according to the rules in force.

Applications from other participants will be considered after the last day of enrollment.

Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.