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Backward stepwise analyses.
Backward stepwise analyses, adjusted for sex.
The backward stepwise analyses showed associations at a level of p < 0.1 for nationality, education, extensive disease, hormone therapy, being free of disease, the physical dimension score (SIP), global health (EORTC-QLQ-C30 score), work demands, and current work ability compared to life time best score (WAI).
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Tables 2 and 3 shows the multiple backward stepwise regression analyses to determine factors independently associated with the EQ-5D dimensions and EQ-VAS.
Separate multivariate backward stepwise regression analyses with further adjustment for cancer-related factors, were also carried out to explore differences in stress levels within the mother and father dyads caring for a child with cancer.
All variables that showed a statistically significant correlation with fecal calprotectin by univariate analysis were subsequently analyzed together in forward and backward stepwise, multivariate regression analyses, after log transformation of fecal calprotectin values.
Backward stepwise (Wald) regression analyses were performed, with hospital mortality as outcome variable.
Simple binary logistic regression and backward stepwise multiple logistic analyses were performed to identify factors influencing high psychological distress.
Multiple forward and backward stepwise logistic regression analyses were then performed to identify independent predictors of SNB positivity, RFS and OS.
Backward stepwise logistic regression analyses were performed, including all variables for retest rate, and for positivity variables with a p-value for the likelihood ratio test of < 0.2.
Next, we performed forward and backward stepwise multiple regression analyses to identify the variables that could best predict the health status and dyspnea scores, using the measurements of pulmonary function, IOS and CT as independent variables [ 6].
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