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GWAS have successfully identified many novel genetic loci associated with complex traits using a univariate regression-based approach.
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Statistical analysis was carried out by using a univariate regression analysis.
The four components were assessed for the likelihood of an association with the residentsʼ perception of their confidence for teaching skills using a univariate logistic regression analysis.
Factors influencing the GGT level were determined using a univariate linear regression analysis.
Differences in proportion G. duodenalis positive between groups were assessed using a univariate logistic regression.
Each covariate was also evaluated using a univariate Cox regression analysis.
The association between the different indices and OS was evaluated using a univariate Cox proportional hazards regression model.
Background was determined using a regression-based background mapping method.
We used a regression-based approach to identify potential SFPs.
To identify prognosis factors, a univariate analysis was conducted using a logistic regression test.
Factors most highly associated with uterine rupture were identified by using univariate regression analysis.
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