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Methods of measuring the regression accuracy in both scenarios are introduced.
For measuring the regression performance of the five compared association models, we use a 5-fold cross-validation strategy by computing the Pearson's correlation coefficient (CORR) and the root mean square error (RMSE) between the predicted and the actual SNP values, which are reported in Figure 1.
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We determine the quality of the fit by measuring the R regression correlation coefficients between the fit and the measured data (indicating on the strength of association between the experimental measurement and the fitted variable).
Ease of learning: We compare the performance between blocks of trials to evaluate whether the user improves by measuring the slope of the regression line between blocks of trials.
They are usually easy to interpret, with the regression coefficients measuring the increase rates of response variables with changes of covariates.
Table 3 shows the results for the linear regression measuring the effect of household income on adult BMI in 2000.
Thus each line of Table 7 in the Appendix is a separate regression measuring the effect of joining a TWA in year 2002 on subsequent labor market outcomes.
The concentrations of MOX and CEF were calculated from their corresponding regression equations measuring the intensity of signals at 359.3 nm and 269.6 nm respectively.
The hGM-CSF concentrations of the tested samples were measured by the regression analysis with the CVXPT32 software.
Association was measured with the regression coefficient.
Bias of genomic predictions was measured as the regression of DRP on the genomic predictions [ 32].
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