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hConvergent validity expresses the degree to which a latent variable explains the variance of assigned indicators.
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.
Since ePPID explains the variance of protein evolutionary rate over three times higher than does the number of binding interfaces, we conclude that ePPID predicts protein evolutionary rate better than the number of binding interfaces.
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Furthermore, the amount of weather variable that can explain the variance of headache events also varied.
It was helpful to explain the variance of criminal incident probability.
Below we compare how different factors can explain the variance of social support in different cities.
All of the two independent variables related to teacher competency, can jointly explain the variance of learning achievement for 6.10percentt.
We compare how different factors can explain the variance of shared fear in different cities by using linear models.
Thus a factor is disregarded unless it can explain the variance of at least one variable (eigenvalue higher than 1).
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