Meta-Analysis of Observational Data

Tuesday, June 12, 2018 and Wednesday, June 13, 2018 8:30 AM - 12:30 PM

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Course Description

Meta-analyses of data arising from systematic reviews are increasingly used for evidence-based clinical and public health practice. Health-care professionals need to understand and critique this research design.

This course will present a detailed description of the meta-analysis process, discuss the strengths, potential bias and limitations of this design, and provide step-by-step guidance on how to actually perform and report a meta-analysis.

We will focus on issues relevant to meta-analyses of observational studies although the overall methodology is highly applicable to meta-analyses of randomized trials as well. In particular, there will be discussion about issues such as adjustment for confounders, aggregating data from different observational designs, assessing small-study effects.

Course Objectives

By the end of the course, students will be able to:

  • Understand the specific methodological issues raised by meta-analyses of observational studies
  • Understand the principles of fixed-effect and random-effects models
  • Examine sources of between-trial heterogeneity
  • Assess small-study effects
  • Incorporate risk of bias assessments into synthesis


All participants should bring a laptop, with Stata software installed. Basic knowledge of Stata is desirable.

Course Reading List
  • Hartung J, Knapp G, Sinha BK. Statistical Meta-Analysis with Applications. Wiley. 2008
  • Schwarzer G, Carpenter JR, Ru┬Ęcker G. Meta-Analysis with R. Springer 2015


Anna Chaimani

Anna Chaimani is a Junior Chair at Paris Descartes University. She studied mathematics and then obtained a MSc in Biostatistics from the University of Athens in 2011 and a PhD in Epidemiology from the University of Ioannina School of Medicine, Greece in 2014. Her research interests focus on methodology for pairwise and network meta-analysis. She has worked on models for small-study effects for network meta-analysis and network meta-epidemiological models. She also works on software development for meta-analysis and she is the author of the network graphs package in Stata. She is a close collaborator of the Comparing Multiple Interventions Methods Group of The Cochrane Collaboration and has worked on the incorporation of network meta-analysis in Cochrane Reviews including the preparation of a new chapter for network meta-analysis in the Cochrane Handbook for Systematic Reviews of Interventions. She has published to date 25 peer-reviewed articles indexed in PubMed.

Course Fee

Registration for this course is $400.00



The registration period has closed for this event.


Hammer LL106

Hammer Health Sciences Building
701 West 168th Street
New York, NY 10032

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