Statistical interaction may occur when we take into account the connection between three or more variables’ and report a situation in which the effect of the two variables done at the same time on the third one is not improved. When interaction occurs between two variable of interest’ the connection among each of the interacting variables and a third 6 dependent variable6 rely on the value of the interacting variable and this makes it harder to anticipate the outcomes of the value of variable that changes especially if the variable it interacts with are difficult to measure (Eastom & Mc Coll, 2014).
When two or more independent variables are involved in a research design, there is more to consider than simply the “main effect” of each of the independent variables (also termed “factors”). That is, the effect of one independent variable on the dependent variable of interest may not be the same at all levels of the other independent variable. Another way to put this is that the effect of one independent variable may depend on the level of the other independent variable.
In order to find an interaction, you must have a factorial design, in which the two (or more) independent variables are “crossed” with one another so that there are observations at every combination of levels of the two independent variables.
For example, when a nurse is administer a blood thinner to a patient the nurse has to be careful about of some of other medication that this patient is taking.such as vitamin k and food like green vegetable because those things can interact with that blood thinner , decrease the effect of the drug and furthere more be life threathining for that patient. Usually, if the issue is not caught by the doctor and the nursing team, pharmacy will call for change of medication because of interaction.
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