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Parameters of items were estimated by maximum likelihood with standardized errors (MLF), implemented in Mplus software (v. 7.11), and integration algorithm (Monte Carlo).
In order to compare kriging results associated with three hypotheses of space time random field decomposition, correlation coefficients and standardized errors between true values and predicted ones are computed.
For factor one, loadings varied between.54 and.71 (standardized errors were.015 to.020), for factor two between.63 and.79 (.011 to.018), and for factor three between.52 and.74 (.014 to.020).
The estimates were the values that minimized the square root of the sum of standardized squared errors (RSE) and/or the square root of the sum of squared standardized errors (RMSE).
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Finally, we calculated from these results standardized (s' and β') and transformed (s-avgdif and β-avggrad) selection coefficients along with standardized standard errors.
B: coefficient, S.E.B: standardized error of coefficient, Beta: standardized regression coefficient.
Absolute standardized error of test samples plotted against their K j values.
The Poisson regression is thus heteroskedastic and so the standardized error estimation was used to correct for heteroskdasticity3.
Most of the predictions had good accuracy, them being within two units of standardized error and high reliability.
Generally, a standardized error of two/three units is usually considered as a warning value for outliers detection.
The absolute standardized error for sample 33 was quite higher as compared to the remaining three samples.
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