Sentence examples for deviations from assumptions from inspiring English sources

We also consider that the EQCM analysis may include too many deviations from assumptions for accurate estimation of mass with the conditions studied.

Because of the added complexity in adaptive enrichment designs compared to standard designs, it may be of special concern how sensitive the trial performance is to deviations from assumptions.

Before using parametric statistical methods to test for differences among groups, data were examined for deviations from assumptions for normality.

Residuals were checked for normality and homoscedasticity but no deviations from assumptions were detected.

Although, rank based correlation methods, such as the Spearman correlation, have been used to reduce the prevalence of spurious correlations due to deviations from assumptions of normality in expression data, we have observed in practice that the Spearman correlation coefficient performs similarly to the Pearson when comparing with MMC (data not shown).

The overall structure of the model we propose, i.e. two distinct impairments linked to functional limitations, is thus likely to be unaffected by this deviation from assumptions.

Analyses carried out by Barot et al. (2004) examined the impact of deviations from these assumptions on results and showed that modest violations of these assumptions had no significant effects on the estimation of DemPMRN.

We concentrated on justifying the distributional assumptions in the count response situation, that is, checking deviations from the assumptions regarding the stochastic part of the hierarchical model, since there was no evidence for specific prognostic factors or factors for baseline adjustment, which would improve the precision of the results when considered in the model.

In many situations, the designed detector based on the nominal assumptions may suffer a drastic degradation in performance even with small deviations from the assumptions.

Some of these assumptions are relaxed in the original treatment, e.g. the lack of excess micromotion [27]; nonetheless, deviations from these assumptions can become important.

The performance of multilayer perceptron (MLP) and that of linear regression (LR) were compared, with regard to the quality of prediction and estimation and the robustness to deviations from underlying assumptions of normality, homoscedasticity and independence of errors.