XClose

Short courses

Home
Menu

Dealing with Missing Data in Research Studies: an Introduction

  • 5 hours (one day), or 8 hours (two days)
  • 1 or 2 days (day 2 optional)
  • 11 Nov 2019

Overview

This short course looks in depth at the problem of missing data in research studies.

You'll learn about different types of missing data, and the reasons for this, along with good and bad methods of dealing with them.

It runs over one full day, with an optional second half day on practical application using SPSS.

This course is delivered by the Centre for Applied Statistics Courses (CASC) - part of the UCL Great Ormond Street Institute of Child Health (ICH).

Course content

Missing data are very common in research studies, but ignoring these cases can lead to invalid and misleading conclusions being drawn.

This workshop gives you guidance on how to deal with missing values and sets out the best ways of analysing an incomplete dataset.

The first day 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 second (optional) day of the course, you'll put the first day's theory into practice using SPSS (v.17 or later) and real-world datasets - particular emphasis is given to multiple imputation.

Learning outcomes

By the end of this course you should be able to:

  • understand the different types of missing data
  • understand the advantages and disadvantages of some of the most commonly used, but less effective, applied methods of dealing with missing data
  • understand the underlying theory of the principled methods of dealing with missing data
  • be able to fully interpret and apply multiple imputation
  • fully understand the advantages and disadvantages of multiple imputation

Certificates

You can request a certificate of attendance for this course once you've completed it. Please send your request to ich.statscou@ucl.ac.uk

Include the following in your email:

  • the name of the completed course for which you'd like a certificate
  • how you'd like your name presented on the certificate (if the name/format differs from the details you gave during registration)

Cost and concessions

The fees are as follows:

  • External delegates (non UCL) - £150 (£225 for both days)
  • UCL staff, students, alumni - £75* (£112.50 for both days)
  • ICH/GOSH staff and students - free    

* valid UCL email address and/or UCL alumni number required upon registration

Prices include printed course materials, refreshments (and lunch for non-ICH participants) 12:45pm - 1:45pm.

Cancellations

We accept cancellations up to five working days before the start of the course with a full refund, though we'd appreciate as much notice as possible to re-allocate the place. Places cancelled or changed after this point won't be eligible for a refund. Please send all cancellation requests directly to the course administrator

Find out about other CASC statistics courses

CASC's stats courses are for anyone requiring an understanding of research methodology and statistical analyses. The courses will allow non-statisticians to interpret published research and/or undertake their own research studies.

Find out more about CASC's full range of statistics courses, and the continuing statistics training scheme (book six one-day courses and get a seventh free.) 

Course team

 Eirini Koutoumanou - Course Lead

Eirini Koutoumanou - Course Lead

Eirini joined GOS ICH in 2008 as the first CASC Teaching Fellow and was promoted to Senior Teaching Fellow in 2014. She has a Bachelor’s degree in Statistics from the Athens University of Economics and Business and a Master's degree in Statistics from Lancaster University, and she's currently studying for a PhD at ICH. Eirini started teaching at ICH straight after her student days, putting into practice and further developing her passion for statistics teaching. She's played an instrumental role in the formation of CASC and hopes to see it develop further.

Learner reviews

"Thank for all efforts and everybody. I think this kind of courses are provided good opportunity to the clinicians to learn statistics, design new studies, interpretation of the results and will improve their research skills."

"Good course to attend."

"Very informative and well-presented course."

Course information last modified: 6 Sep 2019, 15:36