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The proportional hazard assumption of the Cox model was assessed by graphical examination and by goodness-of-fit test (Kleinbaum and Klein 2012).
As important confounding variables, age, marital status, subjective economic condition and satisfaction with present employment status were used and confirmed by goodness-of-fit in the final model using the likelihood-ratio test.
Discrimination and calibration were assessed by goodness-of-fit C-hat statistics and area under the ROC curve.
The fit of the path model was assessed by comparing the expected and observed covariance matrices by goodness-of-fit test, based on chi-square and comparative fit index (CFI) [46] [47].
(iii) Evaluation of component submodels: models were evaluated by goodness-of-fit and individual parameter sensitivity analyses were conducted.
The fit of the logistic regression models and Cox proportional hazard models was evaluated by goodness-of-fit tests.
Model selection was guided by goodness-of-fit plots, pcVPCs, parameter precision, and scientific plausibility.
The observed plasma concentration time profiles of irinotecan and SN-38 were well predicted by this model, as indicated by goodness-of-fit plots.
This fact is confirmed by goodness-of-fit test statistic based on the Rényi Kullback Leibler information.
This may be evaluated by goodness-of-fit plots.
*The models were validated by goodness-of-fit; no interactions were tested.
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