I am a bit confused regarding normality testing for predictor variables in logistic regression.
Example – If I am looking at an older population, and two of the predictors are continuous, fasting blood glucose and high blood pressure, inherently as the population gets older, both endpoints tend to skew to the right. However, if I intend on stratifying each on three levels (high/pre/normal bp and hi/pre/normal diabetes), is it necessary to transform these variables to have a more normal distribution?
I am not sure if this is to improve the linearity of the logIT between the dependent and independent variable.
Best Answer
Having normally distributed predictor variables is not an assumption of logistic regression. Use the predictors as they are, without stratifying them (turning them into categories).