[R] markov models with msm

From: Vassily Shvets <shv736_at_yahoo.com>
Date: Tue 06 Dec 2005 - 09:31:53 EST

I'm working with a dynamic system that I've started to analyse using msm(I've emailed to chris, orignator of the program, separately, but maybe he's on holiday).

The data is obtained from a large cohort of students and consists of a model of learning states that students pass through over a period of one school year. As analyzed with the msm program, the data shows 'no lack of fit' with some covariates that have been included.

Using the msm program gives nice Q and P matrices for the system. Furthermore, the p matrix can be adjusted from t=0 to practically any time range.  However, I'm especially interested in the question of the significance of the covariates in the system:(Pardon me if this question is obvious from the literature; I haven't seen it discussed as yet)can we determine if a dynamic Markov system is homogenous or nonhomogenous on the basis of whether covariates included in the model are significant(as indicated by msm's p-values)? Is this the only way?

One reason I'd like to go further than msm is taking me right now is that this kind of data analysis seems very pertinent in lots of situations, but there's a certain narrowness in msm(look away from it's tremendous precision and other good qualities for a moment): how about situations where people are moving through states that are not consecutive(1 to 5, as opposed to only from one state to the next), as msm seems constrained to limit itself to? I guess I'm also wondering if anyone
has analyzed such empirical data using the state space system in MATLAB or another analysis/simulation program?

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Tue Dec 06 09:38:05 2005

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