How to analyze this data


New Member

I need guidance in analyzing the outcome.

I have 4 independent variables, and 2 dependent variables. The sample size is ~600.

I have two groups: Treatment A and Treatment B. I want to determine if treatment B is better than A in achieving superior outcomes.

The independent variables in each group are #1: Continuous, #2: Ordinal (3 levels), #3:Ordinal (5 levels), #4 Categorical (Yes/No).

The dependent variables are #1: Ordinal (3 levels) ; #2: Categorical (Yes/No)

The dependent variable #1 & #2 is based on the decisions factoring all independent variables.

The dependent variables #1 and #2 are competing goals, i.e., to achieve one, the other sometimes suffers. That is, they are dependent on each other (especially in high-risk cases). In low risk disease, both outcomes are achievable without compromising one another.

I want to know how best to address analyzing this data: What test(s) to use to determine which independent variables have a significant effect on each or both of the dependent variables; Which treatment achieves optimum goals in both the dependent variables. And, How to determine the effect of of one dependent variable on the other.

Thank you


TS Contributor
the second dependent variable cam be clearly analysed using binary logistic regression. Ordinal logistic regression is also a possibility, for the first outcome, but maybe you can simplify your life by turning the 3 levels into two? E.g. by turnig the levels good, neutral, bad into good, not good?

Once you have a model you can use several tools to find an optimum, e.g. Solver in Excel or Optimizer if you work with Minitab.