Abstract
The discrete-time mover-stayer model (Blumen, Kogan, and McCarthy, 1955, The Industrial Mobility of Labor as a Probability Process, Ithaca, New York: Cornell University Press) is a useful model for studying changes over time in heterogeneous populations. Using the EM algorithm, we present an alternative method for obtaining maximum likelihood estimates of the parameters of the mover-stayer model, and consider an extension of the basic model to the problem of incomplete follow-up in panel studies. The models and the methods are illustrated with data from a community-based survey of changes in mental health status over a 1-year period.
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