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The goodness of fit by the two-model analysis was evaluated using AIC.
The relevance analysis was evaluated using two supervised measures: linear correlation and symmetrical uncertainty.
Morphological analysis was evaluated using SEM and chemical composition was investigated by FTIR and XPS.
The discriminative ability of variables identified to predict neurological outcome by multivariate analysis was evaluated using receiver operating characteristic (ROC) curves with the corresponding AUC.
Goodness of fit by nonlinear least squares analysis was evaluated using the Akaike information criterion (AIC) and model selection criterion (MSC).
A new forensic 140-SNP genotyping system from Qiagen, designed for massively parallel sequencing (MPS) analysis, was evaluated using the Ion PGM™ MPS system.
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Loss analysis and thermal analysis are evaluated using the FEA method.
Differences between patients and controls for VBM analysis were evaluated using a general linear model (GLM), through pre-processed images.
Both the signal-to-noise ratio (SNR) analysis and the phase delay analysis were evaluated using dual-frequency (L1 and L2) GPS and GLONASS signals.
Both the SNR analysis and the phase delay analysis were evaluated using dual-frequency GPS and GLONASS signals, i.e., frequencies in the L-band, during a 1-month-long campaign.
All end points in this post hoc analysis were evaluated using a modified intent-to-treat (mITT) population, defined as subjects who had available data for each study week.
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