Article ID: | iaor20091213 |
Country: | Netherlands |
Volume: | 11 |
Issue: | 2 |
Start Page Number: | 121 |
End Page Number: | 131 |
Publication Date: | Jun 2008 |
Journal: | Health Care Management Science |
Authors: | Baker Rose, Jackson Dan |
The synthesis of evidence from trials and medical studies using meta-analysis is essential for Evidence Based Medicine. However, problematical outlying results often occur even under the random-effects model. We propose a model that allows a long-tailed distribution for the random effect, which removes the necessity for an arbitrary decision to include or exclude outliers. In this approach, they are included, but with a reduced weight. We also introduce a modification of the forest plot to show the downweighting of outliers. We illustrate the methodology and its usefulness by carrying out both frequentist and Bayesian meta-analyses using data sets from the Cochrane Collaboration.