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Nicky J Welton
Researcher at University of Bristol
Publications - 287
Citations - 20193
Nicky J Welton is an academic researcher from University of Bristol. The author has contributed to research in topics: Randomized controlled trial & Population. The author has an hindex of 61, co-authored 271 publications receiving 16010 citations. Previous affiliations of Nicky J Welton include University College London Hospitals NHS Foundation Trust & National Institute for Health Research.
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Checking consistency in mixed treatment comparison meta-analysis.
TL;DR: A hierarchical Bayesian approach to MTC implemented using WinBUGS and R is taken and it is shown that both methods are useful in identifying potential inconsistencies in different types of network and that they illustrate how the direct and indirect evidence combine to produce the posterior MTC estimates of relative treatment effects.
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Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves
TL;DR: An algorithm that maps from digitised curves back to KM data by finding numerical solutions to the inverted KM equations is developed, which is a reliable tool for meta-analysis and cost-effectiveness analyses of RCTs reporting time-to-event data.
Journal ArticleDOI
Evidence synthesis for decision making 2: a generalized linear modeling framework for pairwise and network meta-analysis of randomized controlled trials.
TL;DR: Use of the generalized linear model framework allows us to present a unified account of how models can be compared using the deviance information criterion and how goodness of fit can be assessed using the residual deviance.
Journal ArticleDOI
Influence of reported study design characteristics on intervention effect estimates from randomized, controlled trials.
Jelena Savović,Hayley E Jones,Douglas G. Altman,Ross J Harris,Peter Jüni,Julie Pildal,Bodil Als-Nielsen,Ethan M Balk,Christian Gluud,Lise Lotte Gluud,John P. A. Ioannidis,Kenneth F. Schulz,R Beynon,Nicky J Welton,Lesley Wood,David Moher,Jonathan J Deeks,Jonathan A C Sterne +17 more
TL;DR: For each characteristic, average bias and increases in between-trial heterogeneity were driven primarily by trials with subjective outcomes, with little evidence of bias in trials with objective and mortality outcomes.
NICE DSU Technical Support Document 2: A Generalised Linear Modelling Framework for Pairwise and Network Meta-Analysis of Randomised Controlled Trials
TL;DR: This DSU series of Technical Support Documents (TSDs) is intended to complement the Methods Guide by providing detailed information on how to implement specific methods by providing clear recommendations on the implementation of methods and reporting standards where it is appropriate to do so.