The 2022 Statistical Excellence in the Pharmaceutical Industry Award, presented by the Royal Statistical Society (RSS) and Statisticians in the Pharmaceutical Industry (PSI), has been won by Marcel Wolbers, Alessandro Noci, Paul Delmar, Craig Gower-Page, Sean Yiu (Roche) and Jonathan W. Bartlett (University of Bath) for their entry ‘Standard and reference-based conditional mean imputation (methodology and open-source software)’.
The project addresses the need of trial statisticians in the pharmaceutical industry to fully align their analysis strategy with the targeted estimand and flexible missing data assumptions for clinical trials with continuous longitudinal outcomes. The team present a novel imputation procedure which is fully deterministic (i.e. free of Monte Carlo error) and provides treatment effect estimates consistent with the Bayesian approach as well as reliable frequentist and inference with accurate standard error estimation and type I error control. The companion open-source R package ‘rbmi’ is a flexible toolbox to implement these methods in practice.
Read the team’s recent open access article published in Pharmaceutical Statistics in May 2022:
‘Standard and reference-based conditional mean imputation’
, , , , , . Standard and reference-based conditional mean imputation. Pharmaceutical Statistics. 2022; 1– 11. doi:10.1002/pst.2234
Andreas Krause, Editor-in-Chief of Pharmaceutical Statistics, commented: “Very nice to see that Marcel Wolbers, Associate Editor with Pharmaceutical Statistics, and colleagues received the prestigious RSS award for “Statistical Excellence in the Pharmaceutical Industry”. Congratulations, Marcel and colleagues!”