2

There are thirteen predictor variables which are a combination of 8 continuous, 4 binary and 1 categorical variables. The dependent variable is again categorical. I understand that I need to use dummy coding for binary and categorical variables.

How should I model the dependent variable with respect to predictor variables? Which regression model can be used?

soakley
  • 4,341
  • 3
  • 16
  • 27
Shilpi
  • 21
  • 3
  • 1
    The standard regression model in these cases is called : [multinomial logistic regression](https://en.wikipedia.org/wiki/Multinomial_logistic_regression). To my knowledge implementations of it can be found in almost all major packages (eg. R, MATLAB, SAS, etc.) – usεr11852 Feb 05 '16 at 05:42
  • The fact that you have both categorical and numerical predictors is of no consequence, with a suitable response variable, multiple regression could deal with both. However, the fact that the response is categorical is crucial in determining what kinds of analyses may be suitable. – Glen_b Feb 05 '16 at 07:41
  • I tried looking for multinominal logistic regression in R. Initially, I modified my dataset using, mlm – Shilpi Feb 05 '16 at 08:42
  • are your columns independent? see http://stats.stackexchange.com/questions/70899/what-correlation-makes-a-matrix-singular-and-what-are-implications-of-singularit – mandata Feb 05 '16 at 14:20

0 Answers0