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hConvergent validity expresses the degree to which a latent variable explains the variance of assigned indicators.
Its operation can be thought of as revealing the internal structure of the data in a way which best explains the variance.
In forestry literature, the strength of the relationship between MOE and V 2 (or V) has often been cited in terms of the correlation coefficient, r (Eq. 2), or the coefficient of determination, denoted R 2. R 2 (and any variation of R 2) explains the variance of a linear model.
The best model was selected based on Akaike's information criterion (AIC), which compares the adequacy of several models and identifies the model that best explains the variance of the dependent variable as that with the lowest AIC value [74], [75].
We selected the best model using Akaike's information criteria (AIC), which compares the adequacy of several models and identifies the model that best explains the variance of the dependent variable as that with the lowest AIC value.
As demonstrated in the present study, the covariate vigilance explains the variance to a certain extent.
Similar(49)
PCA explains the variance-covariance structure of a set of variables by using linear combinations of those [ 15].
This might explain the variance, but not the decline.
Only about 33.20% of the model can explain the variance.
We now aim to explain the variance among companies.
Furthermore, the amount of weather variable that can explain the variance of headache events also varied.
More suggestions(15)
explains the gap
explains the discrepancy
explains the deviation
explains the variation
explains the distinction
explains the divergence
incorporates the variance
interprets the variance
explains the differentiation
explains the disparity
characterizes the variance
describes the variance
explains the inconsistency
illustrates the variance
examines the variance
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