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Results from per protocol and intention to treat analyses were similar, as were regression models performed with and without bootstrapping.
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In the comparison of models we observed that the hyperbolastic models perform with a greater degree of accuracy than either the Weibull or Gompertz models.
Each model performed with high accuracy and was incorporated into an ensemble model, which performed with the highest overall accuracy of all the models.
In this study we used species distribution modelling, performed with the ecological-niche factor analysis (ENFA) approach.
However, the major analytical tool employed was the Linear Programming mathematical model performed with the Lindo 7.0 computer software.
Similarly on the independent dataset, our model performed with sensitivity values up to 84%.
The predictive model performed with 100% sensitivity and specificity in the training set.
A theory driven model was used to test the research hypotheses using structural equation modelling performed with AMOS 16.0.
Anthropometric data was collected and multivariate regression modelling performed with a view to predicting cervical isometric strength.
In terms of relative RMSE the models performed best with thresholds of around 0.1.
Results: Our models performed well, with cross-validated R values ranging from 0.62 to 0.95.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com