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We specifically aimed to determine the value of adding physiological data and blood data to basic risk adjustment models and to explore whether the risk associated with each model variable was constant across a range of settings or was subject to the constant risk fallacy.
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where is the n-dimensional model variable, is the stochastic variable or parameter, an m-dimensional prescribed i.i.d.i.d
Participants with missing data for a model variable were excluded from the analysis involving that variable.
Specifically, the limiter applied to the turbulence model variables was found to significantly influence the overall convergence behavior.
This set of model variables was then used to calculate exposure.
Collinearity for the model variables was evaluated using variance inflation factors and tolerances.
Estimation of the model variables was obtained with maximum likelihood using individual level data.
The stability of the 12 model variables was assessed in 1,000 bootstrap samples.
The uncertainty in key model variables was examined through the use of one-way sensitivity analysis.
The statistical significance of the model, model variables was determined at the probability (P) of 0.001, 0.01, or 0.05.
Estimation of the individual model variables was performed blinded for the randomisation of the patients for treatment.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com