Abstract
A meta-analysis is a set of techniques used to analyze and combine the results of individual studies to calculate an overall effect estimate. Conclusions from a meta-analysis are devised in a systematic manner that provides concrete evidence for making decisions about medical interventions. In this paper, the popular methodologies of the fixed-effects model and the random-effects model are compared by pooling the effect sizes of the BCG dataset. And the popular tests for heterogeneity are compared based upon the criteria specified by Higgins and Thompson’s.
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Siwach, M., Kapoor, R. (2021). Comparison of Various Statistical Techniques Used in Meta-analysis. In: Bansal, P., Tushir, M., Balas, V., Srivastava, R. (eds) Proceedings of International Conference on Artificial Intelligence and Applications. Advances in Intelligent Systems and Computing, vol 1164. Springer, Singapore. https://doi.org/10.1007/978-981-15-4992-2_5
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DOI: https://doi.org/10.1007/978-981-15-4992-2_5
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