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By satisfying the above three evaluation criteria, the regression analyses were carried out with the best subset method.
Regarding the selection of the predictor subset from the regression analysis, there are many available methods that include stepwise regression method, forward selection method, backward elimination method, and best subset method (Cohen et al. 2003; Miller 1990).
The indexes in the best subset method to evaluate the fitting of the regression model include standard error of the regression, S, the correlation coefficient, R2, and Mallows Cp index (Mallows 1995).
This paper utilized the best subset method to evaluate the importance of the predictors for the thermal expansion coefficient of the steel strand used in the pretressed reinforced concrete structures, and select the proper subset of predictors to develop a regression model with satisfactory predicting ability.
However, the "subset" method coupled with the analysis of evolutionary conservation of co-expression is suitable for studying poorly annotated genes as well.
The following covariates were selected using the best subset method: age, gender, BMI, prior MI, history of diabetes mellitus, reported hypertension, NYHA functional class ≥2, and baseline serum values of HDL and glucose.
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However, in contrast to standard AAMs, we augment the fitting process by imposing constraints obtained from sources such as subset methods [16, 30].
A beam hardening correction was done for relevant radiograms and an iterative OSEM (ordered subsets) method was applied for CT reconstructions.
To account for this variation in our head shape dataset, we used the separate subsets method [44].
Stepwise regression using AIC stopped at the same five-SNP model as the best-subset method, whereas when a P-value of 0.1 was used as a cut-off for removal from the model, the stepwise regression chose an alternative five-SNP model with rs17410577, rs268, rs301, rs10099160 and rs3289.
To find the smallest set of SNPs accounting for the association of the LPL with TG, we used a number of criteria of fit, with both stepwise and best-subset methods.
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