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standard error of estimate
These data allow an in vivo prediction of vertebral body strength using a noninvasive method with a standard error of estimate amounting to less than 0.95 kN.
      
The best formula was: Expected percent dose excretion at 35 min = 79.3[1-e-(0.004798 x ERPF)] with a standard error of estimate (Sy·x) of 5.2% dose.
      
gave the lowest standard error of estimate (Sy·x) of all the methods.
      
Standard error of estimate, bias and imprecision of different methods were evaluated.
      
On an hourly basis, the overall standard error of estimate (SEE) and the absolute relative error (ARE) were 0.06?mm h-1 (41?W m-2) and 4.2%, respectively.
      
In species with a body weight below one kg, the regression line of BMR against weight is best represented by the equation M = 95.8W0.55 (±0.03; standard error of estimate) where M is basal metabolic rate in kcal/day and W is body weight in kg.
      
The median of the absolute values of residuals (observed age minus predicted age) was 0.08 years, with a quartile deviation of 1.59 years, and a standard error of estimate of 1.19 years.
      
The correlations between strength and maximum power were high (r=0.95-0.98, P>amp;lt;0.02), consistent (before and after training) and valid (gain in standard error of estimate of 6 N or 2% of strength).
      
The standard error of estimate (SEM) ranged from 18.1 to 29.9 W, or 5.3 (0.77)% of the criterion value.
      
A stepwise multiple regression, for which r=0.95 and the standard error of estimate=1.6?s, yielded the following equation: K500time(s)=160.60.154×AOD·kg-1-0.250 × Than.
      
R2?=?0.84, 0.93, 0.90 (all P?>amp;lt;?0.01), standard error of estimate (SEE) =?26.8?±?5.2, 12.5?±?5.4 and 9.9?±?5.7%, for single scans taken at 40, 50 and 60% of femur length respectively.
      
A highly significant correlation between BMC and TBBM was seen (r=0.78, P>amp;lt;0.001) with a standard error of estimate (SEE) of 13%.
      
Using mixed parameters, the two models, D and P, give rise to a standard error of estimate of approximately 200?kg?ha-1.
      
Statistical analyses show that with standard error of estimate (SEE) of 2.14 mmHg, the estimated pressure is well within the 95% prediction interval limits of the measured values.
      
For oil, a multiple correlation coefficient (R) of 0.954 and a standard error of estimate (Sy) value of 0.83 were obtained when reflectance was measured at eight wavelengths.
      
Calibration equations incorporating data from three wavelengths (674, 696 and 2100 nm) had an average multiple correlation coefficient (R) of 0.980 and standard error of estimate (SEE) of 3.1 ppm.
      
Measured band areas for samples with known percenttrans content were fit with a second order polynomial, resulting in a correlation coefficient of 0.99998 and a standard error of estimate of 0.11 over the range of 0 to 50%trans content.
      
Lumbar vertebral density predicted femoral neck density with a standard error of estimate (SEE) of 0.07 g/cm2, and femoral neck density predicted lumbar density with a SEE of 0.09 g/ cm2.
      
The variability (S2A) was calculated from both duplicate operator measurements and the standard error of estimate from nonparametric regression of the individual subject series.
      
The correlation between the two methods was very high (r>amp;gt;0.99) and the standard error of estimate was low.
      
 

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