Hi, I am trying to determine if two different predictive variables are independently associated with a binary outcome (mortality). I have 8 covariates that I have controlled for when selecting the model using backwards selection, but want to see if these two variable act independently. When I include an interaction term V1*V2 (or V1 | V2), then neither are significant. If the interaction term is not included then V2 is significant but V1 still is not. This is true when the covariates are included, or when they are not. I think that this means these two are not acting independent of one another, but am not sure. Clinically these variables are not very different, so this would make some sense, but unsure how to explain that in statistical terms. Thanks!
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