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Vår 2015

HEL-8009 Analysis of Incomplete Data and Methods for Imputation - 2 stp

The course is administrated by

Faculty of Health Sciences

Type of course

PhD Course. This course is available as a singular course.

Course contents

Missing data are ubiquitous in medical research, leading to a loss of statistical power and potentially biased estimates. The aim of this course is to familiarize participants with these issues, and statistical methods for handling missing data.

Specifically the course will:

1. Introduce the issues missing data, review common jargon and argue for a principled, systematic approach
2. Briefly discuss the problems with ad-hoc approaches.  
3. Introduce multiple imputation methods for handling missing data in realistically complex datasets
4. Introduce inverse probability weighting and for missing data and contrast it with imputation
5. Illustrate simple approaches for conducting sensitivity analyses for missing data. Computer practicals will use Stata.

Application deadline


Admission requirements

To take PhD courses you need at a minimum a master's degree or equivalent, or admission to a Medical Student Research Program.

For information about how to apply for admission, go to

Objective of the course

The participants will:

Language of instruction


Teaching methods

A mixture of lectures and computer practicals will be given.


The exam will be a take home test evaluated as passed or failed.

The course will be arranged irregularly and no continuation exams will be given.

Lectures Spring 2015
Lectures: 7.4-9.4.2015 Submission deadline for the exam is 30.4.2015