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Effect modification between factors was searched for by testing appropriate interaction terms for statistical significance.
In addition to examining statistical significance and confounding, the effect modification between variables was evaluated by testing appropriate interaction terms for statistical significance.
Effect modification between MDR Acinetobacter reference groups and APACHE and Charlson index variables was evaluated by testing appropriate interaction terms for statistical significance.
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The interactions were tested including appropriate interaction terms in the models.
Differential effects of type 2 diabetes on the probability of arthroplasty in subgroups according to age, sex, and BMI were tested by inclusion of appropriate interaction terms.
For the primary endpoint, interactions between treatment group and baseline HbA1c, and treatment group and baseline vitamin D will be tested by including the appropriate interaction term in the analysis of covariance model.
The presence of heterogeneity of treatment effect (platinum vs non-platinum) between the strata identified by each investigated biomarker was tested introducing the appropriate interaction term into the statistical models.
In addition, we tested for the moderating effect of relevant covariates by fitting appropriate interaction terms in the model.
We evaluated the additive vs. synergistic effects of NT-proBNP and CAC on the endpoints by using appropriate interaction terms and likelihood-ratio tests.
Tests for differences in the absolute treatment effect according to each characteristic (ie, tests for interaction) will be derived from standard tests for heterogeneity/trend across subgroups or, where needed, by fitting appropriate interaction terms with treatment allocation in a linear regression model.
Interactions were examined by including appropriate interaction terms in the Cox regression models.
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