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Thus, indicative of an acceptable fit was validated (Table 4).
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Error in the equation fit is quantified and the fit is validated.
It can be a mistake to declare general availability too early – especially before the product market fit is validated".
Goodness-of-fit was validated by high concordance between observed and expected number of cases in each decile of predicted probability in both training and test samples.
Analysis of variance (ANOVA) of the preliminary fitted model was validated with a confidence level of > 95%.
Models were generated based on training set compounds using the Genetic Function Approximation (GFA) as implemented in the Discovery Studio [57] and the best model (based on the lack-of-fit criterion) was validated with the test set.
The goodness of fit of DBERM was validated using posterior predictive check.
The prediction model was assessed using the receiver operating characteristic curve and the Hosmer Lemeshow goodness-of-fit test and was validated on a new, prospective cohort.
The model was validated as the model fit to validation data was even better than the fit to the calibration target data, exceeding our predefined criterion.
The adapted grammatical reasoning test was validated by fitting the confirmatory factor analysis (CFA) model.
The kinetic formalism was validated by fitting the experimental data from these two independent experiments, rendering a good agreement with the model predictions.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com