regression diagnostics

  1. I

    Linear regression assumption

    How can I handle heteroskedasticity?
  2. C

    Linear Regression: how to tell if factors "disagree"?

    I use a regression as my predictor. Let's say my regression is (y=a1 x1 + a2 x2 + a3 x3) y=a_1 x_1+a_2 x_2+a_3 x_3 I realized that in practise, when my prediction is way off, it's usually because one factor significantly skewed the prediction. For example, x1,x2 are both slightly negative...
  3. S

    Regression diagnostics with proc glm or proc reg

    I fit my model using 'proc glm' but now it seems that proc reg should be used for the diagnostics. So, do I need to fit the model all over again using proc reg and creating dummy variables (that proc glm avoided) since proc reg is to be used for the diagnostics or can diagnostics be done with...