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The clustering of experimental conditions, however, is based on their regression weights.
Risk factors were assigned a score based on their regression coefficient estimate and a total risk score created.
In effect, the probes could be clustered into only two discrete groups based on their regression on to iSDR and oSDR.
The above model was subsequently translated into a mortality risk score, developed on the basis of the respective weights of the significant variables (based on their regression coefficients).
The mortality risk score was developed on the basis of the respective weights of the significant variables (based on their regression coefficients; Table 3) and cutoff points were established by analyzing the ROC curve coordinates for mortality risk according to the products BiXi.
7 Based on their regression model of the observations in this cross-sectional study, at age 70 years, FEV1 would be expected to decrease by about 30% and forced vital capacity (FVC) would be expected to decline by about 20% compared with values at age 20 years.
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Based on their standardized regression weights Odds-Ratio values were computed for those variables included in the equation.
We therefore retained first-order terms in subscale-based regressions solely based on their contribution to the regression as evaluated by the probability of F (enter p ≤ 0.05, remove p ≥ 0.10).
These genes were subsequently ranked based on their absolute Cox regression coefficients, and prognostic models with several sets of top ranking genes using the supervised principal component survival algorithm were developed.
Genes associated with survival (p<0.05) were ranked based on their absolute Cox regression coefficients, and prognostic models with the top ranking genes were developed using supervised principal component survival analysis [16].
We determined the ranks of these genes based on their absolute value of regression coefficient at the minimum mean squared error (MSE) determined by 10-fold cross validation.
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