A frequentist one-step model for a simple network meta-analysis of time-to-event data in presence of an effect modifier.

A frequentist one-step model for a simple network meta-analysis of time-to-event data in presence of an effect modifier.

<h4>Introduction</h4>Individual patient data (IPD) present particular advantages in network meta-analysis (NMA) because interactions may lead an aggregated data (AD)-based model to wrong a treatment effect (TE) estimation. However, fewer works have been conducted for IPD with time-to-eve...

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Bibliographic Details
Main Authors: Matthieu Faron, Pierre Blanchard, Laureen Ribassin-Majed, Jean-Pierre Pignon, Stefan Michiels, Gwénaël Le Teuff
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-01-01
Series:PLoS ONE
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0259121&type=printable
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