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The line regression coefficient (R2) is almost equal to unity, and the slope is very close to unity.
First line: Regression coefficient for change in OR per unit increased, second line: 95% CI.
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Age specific slopes of the lines (regression coefficients) were published, permitting the calculation of the predicted proportional reduction in disease events for any age and blood pressure difference.
Thus, it was possible to draw a graph relating the absorbance versus concentration of KA and calculate the equation of the line and the linear regression coefficient.
A straight line with regression coefficient (R2) of 0.997 was obtained indicating good linearity.
A plot of C/θ vs C (concentration of inhibitor) resulted in a straight line with regression coefficient values close to 1 as shown in Fig. 6, Open image in new window Fig. 6 Langmuir adsorption isotherm plots for MS at different concentrations of FA and EA.
However, across training datasets that included the evaluated line, the regression coefficients were generally relatively consistent within models.
This plot consists of a straight line with a regression coefficient as 0.998.
The obtained plot consists of a straight line with the regression coefficient (R 2) which is almost near to unity.
Regression line: constant + regression coefficient × time (time is defined as; 0 = baseline, 1 = 3 months, 2 = 6 months, 3 = 12 months).
Black lines are the results based on the maximum lagged correlation, and red lines are the regression coefficient in the case assuming zero lag (see text).
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