Introduction to Dealing with Missing Data

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NOTE: This course will be delivered in hybrid mode, i.e. the in-person lecture will be transmitted live on zoom. The face-to-face part of the hybrid courses will go ahead conditional on at least 5 participants registering for this mode of delivery. Few classes may be delivered exclusively online, so please check under the Future dates tab for clarification. The online part of the class will be supported by its own dedicated teaching staff (along with the lead lecturer), therefore participants can expect the same level of group and individual support as the face-to-face class. You will be able to choose your preferred mode of attendance (face-to-face or online) during registration. 

Additionally, we now offer this as a self-paced, online course that you can register for and start at any time. Click below under the 'Online/Self-Paced Materials' tab to register and gain access:

Details

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 software workshop days of the course which will be deilivered exclusively online, the theory is put in practice with the use of SPSS or Stata or R and real-world datasets; particular emphasis is given to multiple imputation. We assume attendees have both a basic knowledge of SPSS or Stata or R if they are attending the optional workshop.

Software requirement:

Everyone attending the SPSS workshop exclusively online 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. We assume attendees have both a basic knowledge of SPSS if they are attending the optional SPSS workshop.

Everyone attending the Stata workshop exclusively online should ensure the Stata software is installed and licensed before attending. Where possible, we recommend using a recent version of Stata for maximum compatibility with the notes provided during the course. We assume attendees have both a basic knowledge of Stata if they are attending the optional Stata workshop.

Everyone attending the R workshop exclusively online should ensure R and Rstudio are installed (installation guidelines will be made available two weeks before the course). Where possible, we recommend using a recent version of R and Rstudio for maximum compatibility with the notes provided during the course. We assume attendees have both a basic knowledge of R if they are attending the optional R workshop

Fees

Course Fees (live)

Below are the course fees for all courses delivered live either face-to-face, or through online video feed.

* 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

Course Fees (self-paced)

Below are the fees for access to the online, self-paced version of this course.

* A valid UCL email address and/or UCL alumni number required. Please note, this category does not include hospital staff unless you have a formal affiliation with the university. To get this discount, please email ich.statscou@ucl.ac.uk to confirm your eligibility and receive a code that can be entered at the checkout.

† If you are a doctoral student from UCL, you can get access to this, and all other self-paced courses developed by CASC by filling in this online form.

Future Dates

‡We recommend logging in 10 minutes prior to the scheduled start time to access materials and ensure the course can start promptly.

Online / self-paced materials

An online, self-paced version of this course is available that includes the following materials:

• Full electronic notes
• Short lecture videos (recorded outside of the classroom) that follow closely with the notes
• Accessible materials with alternative text for images, and captions/transcripts for each video
• Interactive multiple choice quizzes
• Extended practical exercises (with solutions) for further comprehension

Support: The course includes unlimited support through a forum that will be manned by one of our teaching fellows. We aim to provide responses to all questions on Tuesday and Friday each working week. Note that questions can only relate directly to the course materials and should not be used as a consultancy service for your own projects.

Personalised certificates will be generated automatically on completion.

UCL extend: The link below leads to the UCL extend store where this self-paced course is available for purchase. If you are eligible for a discount, then please email ich.statscou@ucl.ac.uk to receive a voucher code that can be used on checkout. UCL delegates should use their university email address to register, and external delegates can use any other account.

Click to register (online / self-paced)

 Alternatively, if you are a doctoral student from UCL, you can get access to this, and all other self-paced courses developed by CASC by filling in this online form.

Feedback

"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!"

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Bespoke courses

If you are part of a team/organisation that would like statistics training, we can arrange extra dates for our existing courses or prepare something more bespoke.

Enquire about Bespoke Courses

Come to 6 day-courses, get a 7th free! 

Once you have attended 6 short-courses, you're ready to claim your 7th day-course for free (please email us to make this arrangement). Our longer introduction course counts as three towards this total.

Contact

Please see our FAQ page before making an enquiry.

Email:
Recommended for general queries/payments:
ich.statscou@ucl.ac.uk

Phone:
For general queries/payments:
+44 (0) 20 7905 2768
To contact a teaching fellow about the contents of a course:
+44 (0) 7730405980

Address:
Centre for Applied Statistics Courses (CASC)
UCL Great Ormond Street Institute of Child Health
30 Guilford Street
London, WC1N 1EH

Other useful links 

• GOS ICH Statistical Support Service
• On-demand UCL Extend self-paced courses
• Royal Statistical Society
• Instats

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