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Proportional hazards assumption was verified by a test based on Schoenfeld residuals.
We assessed the proportional hazards assumption by a test based on Schoenfeld's residuals.
The proportional hazard assumptions were assessed by a test based on Schoenfeld residuals, and no deviations were detected.
The proportional hazards assumption was not violated for MFS, as verified by a test based on Schoenfeld residuals.
The proportional hazards assumption was examined at all stages in two ways: i) visually by inspecting graphs of the cumulative baseline functions against log survival time and ii) by a test based on the Schoenfeld residuals.
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We checked the proportional hazards assumption for this model by using a test based on the weighted residuals and found no evidence of deviation from this assumption.
Robust sensitivity of the residual signals is analysed by means of a test based on the generalised structured singular value.
The fit of the regression models was evaluated by the explained variance of the model and by a permutation test based on a Generalized Goodall's F-Test with 10,000 permutations.
Single representative experiments are shown in Fig. 5. Statistical significance of separation between different condition groups was assessed by a permutation test based on a 1000 random reshuffling of group labels.
Presence of clustering should be tested by a hypothesis test based on an estimate of the variance of the random effect.
The presence of residual spatial autocorrelation was assessed by a permutation test based on Moran's I statistic, which yielded a highly significant p-value of 0.00001.
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CEO of Professional Science Editing for Scientists @ prosciediting.com