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The evaluation of models touches on deep issues in the philosophy of science, because the statistical model often determines how the data-generating system under investigation is conceptualized and approached (Kieseppa 2001).
However, because the statistical model could have resulted in overadjustment, the results were not conclusive.
We did not use PbA observations with missing and zero values of concentration in the analyses because the statistical model described below used a logarithmic transformation.
In addition, 16 loci were scored on the X chromosome, but were not included in this analysis because the statistical model for the X chromosome is currently unresolved.
Caution should be used when modeling DF incidence using statistical relationships with climate variables because the statistical model is trained with present climate data that may differ greatly from projected future climate regimes.
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In the statistical tests of this hypothesis-generation phase, other measures of positive selection where either not strong predictors of eQTLs; or, attempts to utilize measures other than H|H failed because the statistical models did not converge.
Because the statistical models used may be sensitive to extreme values, we excluded 176 extreme blood pressure outliers (> 75th centile+3 × interquartile range) and <(25th centile−3 × interquartile range)) and further excluded 12 men with a recorded pulse pressure less than 10 mm Hg.
Although SW, R, e, and LC have considerable effect on operating speed, but they are excluded from the statistical model, because there is multicollinearity among these independent variables.
No interactions were tested in the statistical model because of the small sample size.
cCould not be determined, as estimates were not reliable because of convergence problems of the statistical model.
Smoking was not included in the statistical model because of a too-low number of smokers in the population to allow calculations.
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