The assumption of linearity pertains specifically to continuous variables entered into any type of regression model. There has to be a linear relationship between these variables and the outcome in both multiple regression and logistic regression.
In order to test this assumption, plot the raw residuals on the y-axis against the estimated outcome on the x-axis. If the assumption of linearity is met, then there should symmetry of points above and below the straight line, with equal derivations across the entirety of the line. However, if there is asymmetry across the line or skewed residuals across the line occurs, then the assumption of linearity is not met.
In order to test this assumption, plot the raw residuals on the y-axis against the estimated outcome on the x-axis. If the assumption of linearity is met, then there should symmetry of points above and below the straight line, with equal derivations across the entirety of the line. However, if there is asymmetry across the line or skewed residuals across the line occurs, then the assumption of linearity is not met.