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metaGLMM - Aggregate-Data Meta-Analysis with Generalized Linear Mixed Models
Extends traditional random-effects meta-analysis by embedding it within a generalized linear mixed-effects model framework. The package supports covariate adjustment and non-normal responses using aggregate data, and provides likelihood-based inference with computationally efficient likelihood evaluation. The underlying methodology is described in Hanada and Sugimoto (2026) <doi:10.1093/biomtc/ujag148>.
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