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In the Example section, we provide an illustration of the models performance using real data from a study in infants with respiratory illness recurrences.
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However, when we assessed model performance using cross-validation, we were able to demonstrate that the commonly-used stepwise model selection approach has inferior predictive performance to approaches that account for model uncertainty.
To ensure that our model was not overfitting the data, we performed fivefold cross-validation within each participant's dataset to determine the model performance using unbiased parameter estimates (see Methods).
3 Our simulation analysis performed the decision tree analysis on MCAR and MAR scenarios to evaluate model performance using a simple, known example of missingness.
Stevens, G. L., Willers, J. L., Sequeira, R. A. & Gerard, P. D. Analysis of deterministic simulation model performance using non-replicated factorial two-level experiments.
Model performance using different combinations of observations is tested against traditionally-derived hydrographs.
We validated model performance using 2852 observed dams across 1947 km of streams.
We developed an approach to evaluate model performance using diverse Fortran compilers on multiple computer operating systems.
Because of the complex nature of the granulation process, the error residual is exploited further in order to improve the model performance using a Gaussian mixture model (GMM).
The goal was to determine the "optimum resolution" at which additional computational efforts do not provide increased model performance using presently available input data.
Evaluation of model performance using AUC revealed some differences among the species.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com