Journal article
Bayesian modelling of lung function data from multiple-breath washout tests
RK Mahar, JB Carlin, S Ranganathan, AL Ponsonby, P Vuillermin, D Vukcevic
Statistics in Medicine | WILEY | Published : 2018
DOI: 10.1002/sim.7650
Abstract
Paediatric respiratory researchers have widely adopted the multiple-breath washout (MBW) test because it allows assessment of lung function in unsedated infants and is well suited to longitudinal studies of lung development and disease. However, a substantial proportion of MBW tests in infants fail current acceptability criteria. We hypothesised that a model-based approach to analysing the data, in place of traditional simple empirical summaries, would enable more efficient use of these tests. We therefore developed a novel statistical model for infant MBW data and applied it to 1197 tests from 432 individuals from a large birth cohort study. We focus on Bayesian estimation of the lung clear..
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Awarded by National Health and Medical Research Council
Funding Acknowledgements
National Health and Medical Research Council, Grant/Award Numbers: ID 1009044, ID 1035261 and ID 1110200; Victorian Government's Operational Infrastructure Support Program; Australian Government Research Training Program