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

@article{Guolo2017RandomeffectsMT,
  title={Random-effects meta-analysis: the number of studies matters.},
  author={Annamaria Guolo and Cristiano Varin},
  journal={Statistical methods in medical research},
  year={2017},
  volume={26 3},
  pages={1500-1518}
}
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
Recent Discussions
This paper has been referenced on Twitter 5 times over the past 90 days. VIEW TWEETS

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 18 extracted citations

Similar Papers

Loading similar papers…