Introduction to Dealing with Missing Data
26 May 2021–28 May 2021, 9:30 am–1:00 pm
This course looks at the problem of missing data in research studies in detail. Reasons and different types of missing data are discussed as well as bad and good methods of dealing with them.
Centre for Applied Statistics Courses
NOTE: Due to the coronavirus outbreak, all courses will now be delivered online through a live video feed. You can expect the same level of group and individual support as you would have received in our face-to-face courses.
Missing data are very common in research studies, but ignoring these cases can lead to invalid and misleading conclusions being drawn. This workshop provides guidance on how to deal with missing values and the best ways of analysing a dataset that is incomplete.
The course runs with an optional day for practical application. The part covers the following topics:
- Reasons for missing data
- Types of missing data
- Simple methods for analysing incomplete data
- More sophisticated methods of dealing with missing data (simple and multiple stochastic imputation, weighting methods)
On the optional day of the course, the theory is put in practice with the use of SPSS and real-world datasets; particular emphasis is given to multiple imputation.
Everyone should ensure the SPSS software is installed and licensed before attending. Where possible, we recommend using a recent version of SPSS for maximum compatibility with the notes provided during the course..
External Delegates (Non-UCL) £150.00 (£225 for both parts) UCL Staff, Students, Alumni £75.00* (£112.50 for both parts) Staff and Doctoral Students from ICH/GOSH FREE †
* Valid UCL email address and/or UCL alumni number required upon registration. Please note, this category does not include hospital staff unless you hold an official contract with the university.
† Limited free spaces available. If there are no free places remaining, Staff and Doctoral Students from ICH/GOSH can still register at the UCL rate.
Cancellations: Cancellation Policy
- Future Dates
Dates Time Apply 26 - 28 May 2021 (28 May, Optional SPSS Workshop) 9.30am - 1.00pm (9.30am -1.00pm optional SPSS Workshop)
‡We recommend logging in 10 minutes prior to the scheduled start time to access materials and ensure the course can start promptly.
"The course was a very thorough introduction to accounting for missing data statistically, going from different types of missing data to simple and then more complicated methods of substitution. It would be very useful for staff who deal with data because it makes you think about importance of good data collection, data types and trial design. I learnt a lot about an area of statistics I had little knowledge of before. It was well taught by an experienced lecturer who explained her subject clearly and made sure everyone in the class was engaged with what she was talking about."
"The pace of the lecture was very good. Although the first half of the day was spent describing methods that should not be used, this was important information. The lecturer was very clear in her explanations."
"Extended my understanding of missing data, and demystified multiple imputation somewhat."
"I thought the presenter was excellent. Very clear and explained everything well. I particularly liked that she asked questions throughout to make sure everyone was understanding the concepts. It made the session interactive and kept me focused."
"Very well structured, good combination of presentations and exercises"
"As a complete beginner to the topic, the content was pitched at exactly right level for me and all very useful. I also really enjoyed the relaxed atmosphere that meant I was extremely comfortable asking any questions and contributing answers."
"Clear and straightforward overview of the topic - really useful intro!"