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To investigate the main determinants of QoL, a multiple lineal regression analysis was performed using backward Wald's criteria, with those variables that significantly correlated with SGRQ total scores.
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Multiple lineal regression analysis was performed to detect differences in knowledge between different departments, physician categories, and country after adjusting by sex and postgraduate education.
A multiple linear regression analysis is performed to benchmark the GP model with a classical technique.
A multiple linear regression analysis was carried out.
These three variables were later introduced as independent variables in a lineal regression analysis with the whole sample and the MCS scale as a dependent variable.
Finally, through the analysis of multiple lineal regression we obtained several statistical models that predict STR, LIN, VCL, ALH, BCF, PC1 and PC2 (the last two variables have been obtained from a principal components analysis) as a function of one, two or three morphometric parameters.
Agreement between PaC02 and PtcC02 was evaluated using lineal regression analysis.
PtcC02 was highly correlated with PaC02 (r = 0.79; p < 0.001), as determined to by lineal regression analysis.
Lineal regression analysis was performed to confirm the association of each of the pathologies independently with the CAT-Health score.
We intended to identify the variables of interest to be introduced in the following lineal regression analysis, trying to find clinical correlates of the HRQOL.
Finally in order to control the confounding effect of co-variables all comparisons between males and females have been conducted using multivariate models (logistic regression for binary variables and multiple lineal regression models for continuous variables).
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