Combining Studies: Practical Meta-Analysis for Beginners
This course provides an overview of meta-analysis from a statistician's point of view, with an optional half day workshop in R and Stata.
Note: This course will be delivered exclusively online via zoom. You can expect the same level of group and individual support as you would have received in our face-to-face/hybrid courses.
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
Meta-analysis is “the statistical analysis of a large collection of analysis results from individual studies for the purpose of integrating the findings” (Glass, 1976)
We introduce the merits of meta-analysis and how it can form an important and informative part of a systematic review. We explain the most common statistical methods for conducting a meta-analysis and common issues that may be encountered along the way. At the end of the course, delegates should be able to conduct a meta-analysis of their own and interpret the results of meta-analyses published in journal articles.
The following topics are covered:
- An introduction to meta-analysis and its place in evidence-based research.
- Outcome measures and extracting relevant data from journal articles
- Fixed effect and random-effects models
- Heterogeneity between studies
- How to identify and deal with publication bias.
Related topics that we don’t cover on this course are (1) how to conduct a systematic search of the literature, and (2) assessing the quality of studies in a meta-analysis.
A basic level of statistical literacy is required as a prerequisite. In particular, delegates should have a basic understanding of standard errors, p-values and confidence intervals. Those who have completed the five-day ‘Introduction to Statistics and Research Methods’ course run frequently by the Centre for Applied Statistics Courses (CASC) team will be equipped.
R supplement (optional)
In the optional half-day of the course (only available in the live version of this course), the theory is put in practice with the use of R (Rstudio) and real-world datasets. A basic knowledge of R programming is recommended as a prerequisite (taught on our course - ‘Introduction to R’ and ‘Introduction to Stata’). If you are not sure whether you have sufficient knowledge in R, please take our short test in the separate tab titled ‘Prerequisite test for R workshop’.
Stata Supplement (optional)
In the optional half-day of the course (only available in the live version of this course), the theory is put in practice with the use of Stata and real-world datasets. A basic knowledge of Stata is recommended as a prerequisite (taught on our course - ”). If you are not sure whether you have sufficient knowledge in Stata, please take our short test in the separate tab titled ‘Prerequisite test for Stata workshop’.Introduction to Stata
Fees
Course Fees (live)
Below are the course fees for all courses delivered live either face-to-face, or through online video feed.
| External Delegates (Non-UCL) | £200.00 (£300 inc. R or Stata supplement) |
| UCL Staff, Students, Alumni | £100.00* (£150.00 inc. R or Stata supplement) |
| 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
Course Fees (self-paced)
Below are the fees for access to the online, self-paced version of this course.
| External Delegates (Non-UCL) | £75.00 (inc. VAT) |
| UCL Staff, Students, Alumni * | £37.50 (inc. VAT) |
| Staff from ICH/GOSH, and doctoral students * | FREE † |
* 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
| Dates | Time | Apply |
| 22 June 2026 (Theory) | 9.30 - 13.00^ | Book Now |
| 23 June 2026 (Theory) | 09.30 - 13.00^ | Book Now |
| 24 June 2026 (Optional R and Stata Workshop) | 9.30- 13.00 , 13.30 - 17.00^ | Book Now |
^ For those attending online, we recommend logging in 10 minutes prior to the scheduled start time to access materials and ensure the course can start promptly at 1.30pm.
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
- 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 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.
Prerequisite tests for R workshop and Stata Workshop
To participate in one of our additional software workshops, we expect you to have enough experience in that software package to complete the following exercise:
R workshop
First, click here to download the dataset we will use for this exercise and save it on your computer. The dataset is stored in an Excel file format (.csv).
Read in the dataset using the function called read.csv.
Using R, find how many rows and columns are in the dataset (using any code/method you prefer).
Calculate the mean of the variable called Start.IgM (hint: use the function called mean).
Create a new variable in the same dataset of the differences between Start.IgM and Stim.2.IgM.
Note: If you are not familiar with the functions read.csv and/or mean, you can view the help files by running the R code help(read.csv) or help(mean)
Stata workshop
To participate in the optional Stata workshop, we expect you to have enough experience in Stata to complete the following exercise.
First, click here to download the dataset we will use for this exercise and save it on your computer. The dataset is stored in an Excel file format (.csv).
Read in the dataset using the command called import delimited
Using Stata, find how many rows and columns are in the dataset (using any code/method you prefer).
Calculate the mean of the variable called Start.IgM (hint: use the command called mean).
Create a new variable in the same dataset of the differences between Start.IgM and Stim.2.IgM.
Note: If you are not familiar with the commands import delimited and/or mean, you can view the help files by running the Stata command help import delimited or help mean
Feedback
“I really enjoyed this course. I didn’t know exactly what to expect but it will be very useful to me. I learnt a lot. Thanks!”
“This was an excellent course, thank you very much.”
“Really relevant course, well put together and delivered.”
“I found the interactive calculations reinforced the learning well.”
“Good course, if there is more interesting courses that can help my PhD, I will definitely attend”
“This was a fantastic introductory course. The content was well thought out and explained very clearly. Also the best explanation of random effects models I’ve heard so far! Thanks for your hard work Dean”
“I found all the interactions with your institution, since of the beginning very oriented to my needs and giving support. Congratulations!”
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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.
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
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
Link
Further information
Ticketing
Open
Cost
£200.00
Open to
All