Ideally, the reconstruction formula is derived by minimizing the expected error variance.
2.
Properties of the VAR model are usually summarized using structural analysis using forecast error variance decompositions.
3.
Also, the area under RROC curves is proportional to the error variance of the regression model.
4.
Good quality measures need to have high satisfaction loadings, good reliability, and low error variances.
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Linear regression assumes homoscedasticity, that the error variance is the same for all values of the criterion.
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Logistic regression will always be heteroscedastic the error variances differ for each value of the predicted score.
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It loaded most highly on satisfaction, had the highest item reliability, and had by far the lowest error variance across both studies.
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It determines how much of the forecast error variance of each of the variables can be explained by exogenous shocks to the other variables.
9.
It is important to notice that the squared residuals cannot be used in the previous expression; we need an estimator of the errors variances.
10.
Variation across raters in the measurement procedures and variability in interpretation of measurement results are two examples of sources of error variance in rating measurements.
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