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Abstract:
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I introduce two analytical methods which extend group-based trajectory models to multivariate outcomes. The first, the marginal developmental trajectory model, identifies latent patterns separately for each outcome, then uses a contingency table framework to identify common combinations of trajectories. The second, the joint developmental trajectory model, considers all outcomes simultaneously to identify combinations of trajectories. I use group-based finite mixture models to identify and describe latent subpopulations for the multivariate outcomes of interest. I apply these methods using data from the National Long Term Care Survey, which measures disabilities in American elderly from 1982 to 2004. Within latent classes, the models clearly illustrate the age of onset and order in which disability patterns typically appear. Finally, I describe how disability is changing over time.
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