Tell me more ×
Cross Validated is a question and answer site for statisticians, data analysts, data miners and data visualization experts. It's 100% free, no registration required.
up vote 0 down vote favorite

I'm currently doing some transitional modelling using a first order markov transitional model to see how patients transition between 2 pre-defined states e.g. Disability and No-disability. I understand that with a markov transitional model, the transition from one state to another at ANY time point (say T) is only dependent upon the previous state (T-1). The model therefore includes a variable that adjusts for a patients previous state.

I've fitted the model for this and obtained the odds ratio (OR) for the transition at the time point of interest; this is fine and can be interpretted. As i mentioned before, the model adjusts for a patients previous state and this variable also has an (OR) in the model output however i am not sure how to interpret this odds ratio? Anyone know how this is interpretted?

share|improve this question
Is the question related to some specific output from a statistical package? If so, a mention of the software and a screenshot of the output may perhaps help. – user28 Jul 27 '10 at 10:48
I'm confused by the question -- "this variable also has"...which variable? – Yaroslav Bulatov Aug 10 '10 at 21:20

closed as not a real question by csgillespie Oct 25 '10 at 10:38

It's difficult to tell what is being asked here. This question is ambiguous, vague, incomplete, overly broad, or rhetorical and cannot be reasonably answered in its current form. For help clarifying this question so that it can be reopened, see the FAQ.

1 Answer

up vote 0 down vote

What do you want to analyze with this model? Currently as you have made it, you can insert a sequence and see whether it comes from this model or not (the odds ratio).

You probably want to predict how the patient develops further. For that you don't need the odds ratio, but basic inference. See also this question

share|improve this answer