To investigate whether SNP associations were restricted to ER-negative breast cancer, we assessed heterogeneity of associations between these two subgroups by using interaction terms between chemotherapy and SNPs, which were evaluated using likelihood ratio tests, comparing models with and without the interaction term.
Bhakat and Das [4, 5] gave the concepts of -fuzzy subgroups by using the 'belong to' relation and 'quasi-coincident with' (q) relation between a fuzzy point and a fuzzy subgroup, and introduced the concept of ( ∈, ∈ ∨ q ) -fuzzy subgroup.
It is worth pointing out that Bhakat and Das introduced the concept of an -fuzzy subgroup by using the 'belongs to' relation and 'quasi-coincident with' relation between a fuzzy point and a fuzzy subset, and gave the concepts of an ( ∈, ∈ ∨ q ) -fuzzy subgroup and an ( ∈, ∈ ∨ q ) -fuzzy subring [7, 8].
Overall and subgroup-specific ZEBOV seroprevalence rates were estimated and potential differences between subgroups were evaluated by using binomial survey-adjusted chi-square tests.
Differences between subgroups were compared by using the χ2 test or Fisher's exact test when the expected number of events was less than five.
Analysis of RFS defined as the time from CR to relapse was performed according to the Kaplan Meier method, and comparisons of outcomes between subgroups were performed by using the log-rank test.
Differences between subgroups were analysed by using the Chi-square test statistic (for categorical variables), the Student t test statistic (for continuous variables), ANOVA for three groups' comparisons, and the Mann-Whitney test statistic (for non-parametrical comparisons).
We assessed subgroup homogeneity by using the generalised score statistic.
Differences in attack rates were compared between subgroups of close contacts by using the χ test.
Therefore, changes over time and differences between subgroups will be tested by using the Random Intercept Model.
