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Statistical Methods in Medical Research|June 12, 2023
Methods for comparative effectiveness based on time to confirmed disability progression with irregular observations in multiple sclerosisThomas Pa Debray, Gabrielle Simoneau, Massimiliano Copetti, et al.
Statistical Methods in Medical Research|April 26, 2022
Combining individual patient data from randomized and non-randomized studies to predict real-world effectiveness of interventionsMichael Seo, Thomas Pa Debray, Yann Ruffieux, et al.
Journal of Comparative Effectiveness Research|July 29, 2023
Handling related publications reporting real-world evidence in network meta-analysis: a case study in multiple sclerosisMarissa Betts, Kyle Fahrbach, Binod Neupane, et al.
Multiple Sclerosis (Houndmills, Basingstoke, England)|November 6, 2019
Predicting disability progression in multiple sclerosis: Insights from advanced statistical modelingFabio Pellegrini, Massimiliano Copetti, Maria Pia Sormani, et al.
Statistical Methods in Medical Research|August 5, 2016
An overview of methods for network meta-analysis using individual participant data: when do benefits arise?Thomas Pa Debray, Ewoud Schuit, Orestis Efthimiou, et al.
Statistical Methods in Medical Research|July 24, 2018
A framework for meta-analysis of prediction model studies with binary and time-to-event outcomesThomas Pa Debray, Johanna Aag Damen, Richard D Riley, et al.
Journal of Comparative Effectiveness Research|January 23, 2024
Visualizing the target estimand in comparative effectiveness studies with multiple treatmentsGabrielle Simoneau, Marian Mitroiu, Thomas Pa Debray, et al.
Journal of Comparative Effectiveness Research|September 1, 2017
Practical implications of using real-world evidence (RWE) in comparative effectiveness research: learnings from IMI-GetRealAmr Makady, Heather Stegenga, Antonio Ciaglia, et al.
Multiple Sclerosis (Houndmills, Basingstoke, England)|April 7, 2022
Recommendations for the use of propensity score methods in multiple sclerosis researchGabrielle Simoneau, Fabio Pellegrini, Thomas Pa Debray, et al.
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