Statistical interaction can happen in a two-way ANOVA. It is possible for variables to work independent from one another within a study. When this happens, there is a need to consider the interaction between the variables. A statistical interaction occurs when the effect of two variables working together causes a greater change or a lesser change, than is anticipated. The variables are somehow dependent on one another. You will have to know the levels of each variable to understand the effect on the data. The independent variables are creating a greater effect on the dependent variable. The independent variables are not affecting each other. The study for exercise 18, researchers collected data from family members regarding level of care in Hospice with LPC, hospital with LPC, and hospital without LPC. The family members did not report a change in the level of care within the hospital with LCP vs. hospital without LCP comparison. When the hospice vs. hospital with LCP or the hospice vs. hospital without LCP groups were compared, there was a significant difference. Differences in the level of care was indicated by the p < alpha. LCP and hospice, and LCP and hospital seem to interact with the level of care (Grove & Cipher, 2017).
Interaction is a kind of action that occurs as two or more objects influence one another. The idea of a two-way effect is essential in the concept of interaction, as opposed to a one-way causal effect combination of many simple interactions can lead to surprising emergent phenomena. Interaction has different tailored meanings in various sciences. All systems are related and interdependent. Every action has a consequence.
In statistics, an interaction is a special property of three or more variables, where two or more variables interact to affect a third variable in a non-additive manner. In other words, the two variables interact to have an effect that is more than the sum of their parts.
For example, two of my friends are on weight loss program. We’re evaluating 2 different diets and 2 different exercise programs. One focused on cardio and one focused on weight training. We want to determine which result in greater weight loss. We randomly assign participants to either diet A or B and either the cardio or weight training regimen, and then record the amount of weight they’ve lost after 1 month.
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