Sentence examples for means predicted by from inspiring English sources

Predicted mean severity levels (and 95% CI) for different combinations of Likert scale levels of the three descriptors are shown in table 7. Relationships between actual mean overall assessments of severity (VAS) and means predicted by the model are shown in figure 4. When individual assessments were compared with predicted values, the pR was 0.78.

Estimated marginal means predicted by these linear growth models were used for graphical representation of adiponectin trajectories.

The better models chosen were evaluated by a simple regression analysis and means predicted vs. determined by DXA were compared to verify the accuracy of the equations.

Fig 2 shows the agreement between mean observed risk and mean predicted risk by 5 year age bands for both men and women.

This value is 2.1‰ greater than the global mean predicted by Farquhar et al. [7], for the sites of enrichment of 4.4‰, but in agreement with the global average leaf water δ18O means of 6.1 6.8‰ (also flux weighted) predicted to be necessary to explain the Dole effect [6].

The data were assumed to be log-normally distributed with a geometric mean predicted by the model and a geometric standard deviation (SD) computed from the arithmetic SD given for each data point by Haddad et al. (2000).

Fig 1 visually shows the agreement between mean observed risk and mean predicted risk grouped by tenths of predicted risk for all three models.

Notes: Conditional means are predicted by an OLS regression model of mother's years of schooling on child's birth months (effective coding) for urban and rural samples separately.

These measures quantify the degree to which the dose-group means that are predicted by the model differ from the actual dose-group mean, relative to the amount of expected variation in the dose-group means.

Due to the prime importance of mean parameters in HMM-based speech synthesis [47], we investigate the difference between mean values predicted by two systems.

The outputs of trained NNs have high correlation with the desired values and the foEs yearly mean values predicted by NNs have good agreement with the observed data.