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The effect of Alu density on mutation feature based classification (a binary variable) was analyzed using a logistic regression model.
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Binary variables were analyzed using Fisher's exact test.
Binary variables were analyzed using method of Nagelkerke et al. (10).
Binary variables were analyzed with Fisher's exact test and survival proportions between groups were analyzed with the log rank test.
When comparing the baseline characteristics and the outcomes between the two groups, continuous and ordinal variables were analyzed using Mann-Whitney test, and binary variables were analyzed using χ trend test or Fisher's exact test.
The association between diagnostic groups and each outcome variable was analyzed using ordinal or binary logistic regression.
Association of the variant with ER/PR status controlling for other patient and tumor variables was analyzed using binary logistic regression.
The influence of sex in the associated variables was analyzed by using a multivariate binary logistic regression model.
As an alternative indicator of small mammal abundance in the study villages, the reported sighting of small mammals (commonly referred to locally as "rats") in the household within the previous 2 weeks, treated as a binary variable, was also analyzed.
Differences between groups for categorical variables were analyzed by binary logistic regression.
Differences between groups for the distribution of categorical variables were analyzed by binary logistic regression.
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