Interaction effects occur when the effect of one variable depends on the value of another variable interaction effects are common in regression analysis anova and designed experimentsin this blog post i explain interaction effects how to interpret them in statistical designs and the problems you will face if you dont include them in your model. In an empirical analysis the assessment of statistical interaction depends on the type of outcome variable and the corresponding statistical model linear regression poisson regression and survival analysis are the standard statistical models for continuous count and survival outcomes respectively. In practice the benefit of cardiovascular medicines is less consistent than it is in clinical trials this is due to multiple uncontrolled factors that co determine the efficacy of the new treatment in statistical terms they interact with the new treatment interaction effects are rarely assessed . What association and interaction describe in a model the following examples show three situations for three variables x1 x2 and y x1 is a continuous independent variable x2 is a categorical independent variable and y is the dependent variable
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