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Academic Lead: Dr John Hodsoll 

Date: 21st November 2018

Time: 09:00-17:30

Venue: Computer Room A & B, Main Building. Institute of Psychiatry, Psychology and Neurosciences (IoPPN), King's College London. View Map.


  • External £150
  • KCL Staff £112.5
  • KCL Student £75
  • King's Health Partners £112.5
  • Other student £112.5

Last booking: 18th October 2018

BOOKING: Booking for this course has now closed. 



Students should have a basic understanding of applied statistics (e.g. confidence intervals, t-tests), experimental design and the statistical software STATA (such as can be gained from the BHI Introduction to Programming course running in October). Some understanding of random effects would be useful (such as can be gained from the BHI Introduction to statistical modelling course running in January) but will be revised within the course.


This course is designed to introduce students to the statistical techniques used in meta-analysis, the synthesis of data from different studies. It will enable participants to utilize these techniques in their own meta-analyses and facilitate the interpretation and critique of existing meta-analyses. Practical examples will be drawn from the mental health field. Upon completion of this course it is intended that students will be able to:

  • Calculate the statistical tests to run a meta-analysis under different settings and assumptions;
  • Know how to run a variety of common meta-analyses; for single-group means, two-sample mean differences (independent and dependent), two-group binary outcomes and correlation coefficients;
  • Understand and be able to explain the difference between fixed-effects and random-effects meta-analyses and choose which is appropriate in relevant contextPerform a meta-analysis when outcome metrics differ across studies;
  • Assess heterogeneity across studies;
  • Understand and calculate the following statistics data: Cohen’s d, Hedges g, risk ratio, odds ratio, risk difference, Fisher’s z, T-squared, Q, I-squared;
  • Use a funnel plot to assess publication bias.


Please note the following:

If you would like to pay by internal transfer, please contact

Your place will not be confirmed until payment has been made.

Failure to cancel without sufficient notice will forfeit your course fee and access to future courses.

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