Network Meta-Analysis (NMA) Methodology

This skill equips Claude with deep expertise in Network Meta-Analysis (NMA) methodology, enabling it to assist researchers and data scientists in planning, executing, and reviewing complex indirect treatment comparisons. It covers critical theoretical foundations like transitivity and consistency assessment, offers practical code snippets for R packages like netmeta and gemtc, and ensures adherence to reporting standards like NICE DSU and PRISMA-NMA. Use it to select between fixed and random effects models, interpret treatment rankings using SUCRA or P-scores, and troubleshoot statistical inconsistencies in multi-arm trial networks.

Key Features

Use Cases