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Moreover, separate CIs of the predictive value within each scoring method are presented.

Characteristics of the PRO instruments, including the number of items, concepts measured, and scoring method, are presented in Table  2.

Results from the final IRT calibrations for the reduced item set are shown in Table 5. Note. a represents the slope parameter estimates and b represents the difficulty parameter estimates The means and standard deviations of the PMH subscales and the overall scale scores, using the new scoring method, are presented in Table 6.

In Phase 2: 1) An algorithm is proposed and implemented for negation phrases identification; 2) A mathematical approach is proposed for sentiment score computation; 3) A feature vector generation method is presented for sentiment polarity categorization.

Furthermore, a new discriminative likelihood score weighting technique was proposed for speaker identification, and a likelihood score weighting method was presented for the speaker identification task [24].

A novel two-stage discriminative score normalization method was presented in [89].

A total scoring method was performed in this scale.

In both instruments, an additive total scoring method was used.

In the present study, the standard binary scoring method was used [ 112], for which items are scored as 0-0-1-1 0-0-1-1 0-0-1-1 0-0-1-1

The scoring method was Butler.

The agreement values of all SQIs for the non-linear scoring method were higher than the linear scoring method.

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