Table 2 summarizes the classification accuracy, sensitivity and specificity of discriminant analysis using different combinations of regional DVR estimates as predictor variables.
Incorporating all these regional DVR estimates as predictor variables in discriminant analysis yielded accurate classification of control subjects and AD patients with high sensitivity and specificity, and the results agreed well with those using the cerebellum as the reference region.
The performance of discriminant analysis was evaluated with different combinations of regional DVR estimates as predictor variables and the chi-squared (χ 2 ) test was used to examine the overall accuracy in classification and prediction of group membership using the discriminant functions [ 23].
The US currently estimates national DDW carbon stocks using models with standing live tree attributes as predictor variables, calibrated using preliminary DDW field estimates.
Random intercepts and fixed effects of average odor ratings of 1 to < 2, 2 to < 3, 3 to < 5, and ≥ 5 compared with no odor were estimated as predictors of activity limitation due to odor, coded as a 0/1 variable.
When prenatal BPb, average childhood BPb, and 78-month BPb were estimated as predictors of delinquent behavior, increasing concentrations were associated with a modest increase in delinquent acts reported in adolescence.
Specifically, I used a general linear model with the contrast of interest as the response variable, and the estimated SA as predictor.
If these hypotheses were not rejected (P>0.05), then, to avoid over-fit bias (Abrahamowicz and Ciampi, 1991) and adhere to the model parsimony principle, the predictor effect was estimated as, respectively, constant-over-time HR and/or linear function.
Human intestinal absorption (HIA) is also estimated, as a predictor for oral bioavailability.
In Fig. 2b the blue line plots the probability, at each step, that a model generated from random data has a mean-squared error (MSE) as low as the observed model; the red line plots P-values generated by proportional hazards regression using the biological age estimate as a predictor of mortality.
To assess predictive validity, we used a general linear model with the contrast of interest as the response variable, and the estimated SN activity as predictor.
