I am working on a population-based study including two waves (baseline and follow-up).
My variable of interest is computed using the two waves, and is the difference in renal function between follow-up and baseline (Delta = follow-up - baseline).
Renal function normally...
I was thinking of a model with 5-6 covariates, with a sample size of >300.
I know that for homoscedasticity assumption, no pattern should be observed for residuals (y) vs. fitted (x), with no funnel, but wasn't sure for linearity in a multiple regression setting.
I would like to know how can one test the linearity assumption in a multiple regression model?
I know that for a simple regression, this assumption is tested visually by examining the scatter plot between X = predictor Y = outcome, with the dots forming an ellipse and being aligned on...