Flexible random-effects distribution models for meta-analysis

@article{Noma2020FlexibleRD,
  title={Flexible random-effects distribution models for meta-analysis},
  author={Hisashi Noma and Kengo Nagashima and Shogo Kato and Satoshi Teramukai and T. A. Furukawa},
  journal={arXiv: Applications},
  year={2020}
}
In meta-analysis, the random-effects models are standard tools to address between-study heterogeneity in evidence synthesis analyses. For the random-effects distribution models, the normal distribution model has been adopted in most systematic reviews due to its computational and conceptual simplicity. However, the restrictive model assumption might have serious influences on the overall conclusions in practices. In this article, we first provide two examples of real-world evidence that clearly… Expand
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