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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.
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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).
Any deviation from these assumptions may drastically hamper the person's effectiveness not because of any inherent barrier to interaction, but because of a mismatch between the person's effective abilities and the assumptions underlying the interface design.
Robust statistics, more specifically, the stability theory of statistical procedures, systematically investigates the effects of deviation from modeling assumptions [17 19].
The residual analyses indicated no major deviation from the assumptions of linear regression.
Any deviation from these assumptions would be expected to degrade the log-normal approximation.
We found little deviation from these assumptions in the residual analysis of the transformed SIR data (Zi's).
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