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Modelling error was accounted using the Generalised Likelihood Uncertainty Estimation (GLUE) methodology.
Model conditioning was assessed using the Generalised Likelihood Uncertainty Estimation procedure.
Model performance was evaluated by considering uncertainties in model inputs using the Generalised Likelihood Uncertainty Estimation (GLUE) procedure.
The temporal variability and the uncertainty of the rating curve and its parameters were analysed through a Monte Carlo (MC) analysis on a moving window of data using the Generalised Likelihood Uncertainty Estimation (GLUE) methodology.
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We used the Generalised likelihood-ratio test as a testing procedure.
To examine changes in the likelihood of fatigue, depressive symptoms, and chronic disease, we applied a repeated measures logistic regression analysis by using the generalised estimating equations method with autoregressive correlation structure, as in our earlier papers.
An analytical formula for critical pressure has been derived using the generalised Galerkin method.
We assessed subgroup homogeneity by using the generalised score statistic.
Our analysis used a fixed effects meta-analysis using the generalised inverse variance method.
Comparison between survival curves was made using the generalised Wilcoxon's test.
Here we employ the Generalised Likelihood Uncertainty Estimation (GLUE) method to address these issues.
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CEO of Professional Science Editing for Scientists @ prosciediting.com