I have collected people's reactions to pictures (rating 0-100). The pictures are either greyscale or in colour (categorical predictor) and they vary in resolution (continuous predictor). I want to use colour and resolution to predict the rating with a linear model:
lm(rating ~ colour * resolution)
However, when I performed a t-test to see whether colour predicts resolution, I found a significant difference with greyscale pictures having a higher resolution than colour pictures.
Is the dependence from one predictor on the other a problem for the linear model?
If yes, what could I do to rectify this situation?
If not and I can still use the linear model, can I still interpret a significant main effect of colour as the effect that is independent from resolution?