This repository contains a Python module (rankagg.py) that implements different rank aggregation methods, ready to be applied to Network Meta-Analysis (NMA) datasets. This module has been used in the notebook in this repository (rankagg_notebook.ipynb), used to produce all the results from Chapter 8 (Rank-aggregation methods for NMA) of Paride Crisafulli's PhD thesis (Applications of computational statistics to healthcare). At the moment (24/05/2026), the thesis has yet to be defended. In the notebook, we use the so-called antipsychotic dataset (leucht_2013.csv), an NMA dataset by Leicht et al.:
Leucht S. et al. Comparative efficacy and tolerability of 15 antipsychotic drugs in schizophrenia: a multiple-treatments meta-analysis. The Lancet, 2013; 382, 951-962. doi: 10.1016/S0140-6736(13)60733-3.