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Using a scaling factor, the peak currents predicted by multiple point regression fall within 10% of the measurements.
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The influence of prognostic factors was analysed by multiple regression and logistic regression.
Changes in primary and secondary endpoints between baseline data and different time points of follow-up will be analysed by multiple linear regression models.
The predictive model was obtained by multiple logistic regression analysis.
Passive respiratory mechanics were measured by multiple linear regression.
The results were analyzed by multiple linear regression.
The correlation was obtained by multiple linear regression.
These correlations were obtained by multiple linear regression.
The data were analysed by multiple linear regression and partial least squares regression analysis.
The data were analyzed by multiple linear regression analysis after univariate analysis.
The effects of SNPs on CH were further investigated by multiple logistic regression.
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