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RI was estimated using the above multivariate techniques based on a number of observed variables iteratively as suggested by Alinovi et al. (2008).
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Multivariate analysis using the above four statistically significant parameters (P<0.05) identified PFTK1 as an independent prognostic factor, in addition to pT, pN, and pM (Table 3).
The multivariate model using the above variables except for LV systolic dysfunction indicated that female gender, the presence of a CES, creatinine, NIHSS score, and WC were significantly associated with NT-proBNP level.
Using the above method: 10x/2 = 5x.
However, the significant difference between high-exposure and low-exposure groups disappeared (adjusted odds ratio = 1.26, 95%CI = 0.76-2.09; p = 0.381) after adding the single variable representing PPE use to the above multivariate logistic regression.
Multivariate analysis was performed by logistic regression using the above-mentioned independent variables and discharge to home as the dependent variable.
Odds ratios for the determinants of chemotherapy use were obtained from the above multivariate logistic regression in which all determinants were mutually adjusted.
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Finally, we used the above-mentioned variables that were significantly associated with 8-oxodG and pregnancy outcomes in a multivariate logistic regression analysis.
Furthermore, to investigate the effect of menopausal status on skin thickening in early disease, we conducted a subsample analysis, using the same multivariate model as specified above, but restricted to women with baseline disease duration shorter than 5 years.
In addition to the univariate analyses, we evaluated the alteration in the cortical currents using the decoding method (multivariate analysis).
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