Combining cross-sectional and prospective data methods to improve transition parameter estimation for characterizing the accumulation of HIV-1 drug resistance mutations.

Abstract excerpt

The order and rate of acquisition of HIV drug resistance mutations have been estimated from longitudinal and cross-sectional data using Markov models and branching trees, respectively. This article proposes methods that make use of both longitudinal and cross-sectional data simultaneously by employing link functions between the two parameter sets. Most functions that link the two parameter sets also depend on the...

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