how to prepare data for calculation of odd ratios?

Question

Hello,

I have large genomics database on two groups of patients (continuous variables). One group developed complication at some point of observation, this group has 4 repeated measures of gene eapression collected. Control group has only 3 time points collected. I would like to know if expression of some genes at baseline (week 0) predict outcomes: comlication (coded yes no) or death (coded 1 or 2). How do I prepare the data for analysis and what model do I choose? Do I need to compare LSmeans per subgroup? In this data I have genes on columns, patients IDs on rows.

Ted · Answer

In JMP you can conduct multi-level logistic regression

https://community.jmp.com/t5/Discussions/Logistic-regression-with-multiple-outcome-variables/td-p/4901

but I would start with a two-level with aggregated data (and would look what will happen):

1. Complications Yes ( Complications Early and Late)

2. Complications No

irinastl · Answer

I have 3 types of role variables, or treatment complications: 1. Early complications, 2. Late complications and 3. No complications. So, Logistic regression wouldn't probably work: I am getting "failed to converge (step-halving limit)" error. The treatment type is the same in both groups. Have anybody used a Partial Least squares for biomarkers prediction for disease outcome?

irinastl · Answer

Our University does not have subscription for JMP Genomics, but thanks for the article.