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Subsequently, we explored independent predictors of discordant ethnicity information by constructing a multivariable logistic regression model with concordant/discordant ethnicity status as the binary outcome variable and self-reported ethnicity as a covariate.
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Variables with p < 0.25 in the simple regression analysis were used for constructing a multivariable regression model to explain herd CM.
Finally, we assessed the joint association of muscle strength and CRF by constructing a joint variable of tertiles of muscle strength and CRF, respectively, and associated that with the outcomes in multivariable models.
Due to the small number of SRs included in this study, we first constructed a multivariable linear regression model by including only language restriction and author contact.
We then constructed a multivariable logistic regression model, first considering variables significantly associated with outcomes in univariate analysis, followed by a search for collinear terms.
We also constructed a multivariable model to evaluate the association between iron deficiency and anemia and vitamin A deficiency and anemia by excluding children with inflammation.
We constructed a multivariable model to identify independent correlates of poor hemodynamic control.
We constructed a multivariable model to investigate the independent association of TIR with survival.
We did not construct a multivariable model because of the relatively small sample size, resultant concerns of stability, and problems associated with overfitting.
We constructed a multivariable model in 115 patients for overall survival including key variables of diagnosis, performance status, stage and the use of systemic therapy following immune assessment.
We then constructed a multivariable logistic regression model to determine the independent and unique associations between the empowerment variables and inadequate use of antenatal care.
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