Let\'s say we\'re trying to figure out if X causes Y and the data consists of 2
ID: 3051967 • Letter: L
Question
Let's say we're trying to figure out if X causes Y and the data consists of 2 prior groups, A and B. Combining the 2 groups can give an overall regression effect that is misleading when there's an 1. Interaction X has a different effect on Y for Group A than it does for group B illustrated by non-parallel within group slopes 2. Confounder A difference between A and B that is influencing both X and Y Plot 1 Plot 2 Plat 3 Plat 4 For each of the 4 plots above (displaying two separate groups) indicate whether they display A Only Interaction B Neither C Only Confounding D Both Plot 1 Plot 2 Plot 3 Plot 4Explanation / Answer
Looking at plot 4 we see there is interaction between the 2 groups
Looking at plot 3 we see confounding
plot 1 is neither and plot 2 is both
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