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Binary logistic regression analysis confirmed intervention effects exceeded confounding effects.
Binary Logistic regression analysis showed that the age, H-Y stage, depression, anxiety and autonomic dysfunction increased the risk of constipation in PD patients.
A binary logistic regression analysis was used to investigate the factors thought to influence immunocompetence.
A binary logistic regression analysis was applied to the data, simultaneously considering five previously known risk factors for rejection.
Binary logistic regression analysis was performed to identify risk factors of headache.
Binary logistic regression analysis was undertaken to identify any association between covariates and outcome (PVA).
Binary logistic regression analysis also shows similar trends in OOPE and CHE.
Binary logistic regression analysis was performed with a forward stepwise entry method.
Table 5 Results from binary logistic regression analysis of playground slide-related injuries.
Also, based on binary logistic regression analysis, predictors for hospital treatment were determined.
Table 6 Variables predicting pertinence to the clinical group Binary logistic regression analysis Predictors* B (e.p).p
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