Sentence examples for score standardization from inspiring English sources
For each test, linear regression was used to investigate the association of group with performance, adjusted for age and gender where score standardization had not already accounted for these factors.
The SF-36 scales were scored using the method of summated ratings which assumes that items within a hypothesized scale can be summed without score standardization or item weighting [ 13].
The scores of the two dimensions and the total SF36 score are based on mathematical averaging of the scale components (summated ratings) which assume that items within a hypothesized scale can be summed up without score standardization or item weighting [ 47].
Too often school nurses are all but forgotten in the education wars over test scores, standardization and vouchers.
Calculating the utility of answers by the z-score standardization avoids a bias of overestimating the answer quality caused by popular questions.
During training stage z-score standardization was applied on these features [ 19].
It is noteworthy that the normalization process between two raw expression datasets was only Z-score transformed, without using log10 transformation before Z-score standardization.
When the distribution of the similarity values is known, several parametric normalization approaches can be applied, e.g., the Z-score standardization for Gaussian distributions.
The SD of the z-score standardization allows comparison of each observation from different normal distributions, and the average of zero avoids introducing aggregation distortions stemming from differences in the normal gene expression means.
Differences in measurement methods between the different cohorts is a limitation to the study that we have tried to overcome by using cohort specific cut-offs for quintiles and z-score standardization.
The above-mentioned use of cohort specific cut-offs and z-score standardization and the relative homogeneity of the individual cohorts have probably reduced the impact of this bias.
