Random-effects meta-analysis: the number of studies matters.

  title={Random-effects meta-analysis: the number of studies matters.},
  author={Annamaria Guolo and Cristiano Varin},
  journal={Statistical methods in medical research},
  volume={26 3},
This paper investigates the impact of the number of studies on meta-analysis and meta-regression within the random-effects model framework. It is frequently neglected that inference in random-effects models requires a substantial number of studies included in meta-analysis to guarantee reliable conclusions. Several authors warn about the risk of inaccurate results of the traditional DerSimonian and Laird approach especially in the common case of meta-analysis involving a limited number of… CONTINUE READING
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