Week9 – Examples

During week 9 , we looked at a number of combinations of logistic regression, different types of explanatory variables.  For this example, let’s look at a dataset where our outcome or response variable has more than 2 levels, a proportional odds model.  The coding we used with Proc Logistic is the same you would use here.

This example has males and females, a number of them have been placed on an active trial whereas others have been placed on a placebo trial.  The outcome variable is called improve and has been classified into 3 levels:  marked improvement, some improvement, or no improvement.  For this example I will provide you with the raw data, you will need to do “something” to the data before analyzing it.

gender treatment improve count
female active marked 16
female active some 5
female active none 6
female placebo marked 6
female placebo some 7
female placebo none 19
male active marked 5
male active some 2
male active none 7
male placebo marked 1
male placebo some 0
male placebo none 10

Is there a different in improvement for individuals on active vs placebo and is there a gender effect?

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