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Given that (mu ) is inconsequential, we fix its true value to 0. We also fix the variance of (u_{t}) to 1 without loss of generality.
To use η3C (in Figure 2) fix the variance of the error on y5 in Figure 2 to be the variance provided by only error-5.
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When block effects are fixed, the variance of the estimated response surface is not uniquely estimated, and in practice this variance is obtained by ignoring the block effect.
For identification of the structural equation models, we fixed the variance of the latent variable to one, and for models with ordinal items the WLSMV estimators were chosen (Muthén and Muthén 1998 2010).
Therefore, if h is fixed, the variance term goes to 0 whereas the bias remains fixed so that the L 2 -risk of the estimate does not go to 0. Consequently, a fixed choice for the bandwidth is not convenient and it is essential to choose h = h ( n ) tending to 0 with n.
If instead the distribution mean γ ¯ is increased keeping γ ^ fixed, the variance increases with γ ¯ toward the HoC value.
The identifiability of the model parameters was ensured by loading each observed variable on only one latent construct and by fixing the variance of each latent variable to one.
24 We fixed the variance to ensure that much lower estimates of quality of life detriment using committee consensus health utility index estimates from an Institute of Medicine report 27 would be the lower 95% centile of the distribution.
Fixing the variance of the Quadratic slope and the covariances between the Quadratic slopes of family members to zero did also not result in a significant drop in fit (Model 3 vs. Model 2: χ(3) = 2.32, ns), suggesting that the Quadratic slope should be interpreted as a fixed factor.
Starting with a two-component mixture, such as the spike slab, we can obtain models with a point of mass at zero and a slab, such as BayesB or –C, by fixing the variance of one of the components at zero (see paths 2a and 2b in Figure 2).
Because the model was identified by fixing the variances of the latent constructs to 1.00, the standardized factor loading for a particular item can be calculated by taking the square root of the item's variance explained by the underlying factor.
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