Semiparametric Mixed Effect Model with Application to the Longitudinal Knee
Osteoarthritis (OAK) Data
Huiyong Zheng, Maryfran Sowers, Carrie Karvonen-Gutierrez, Jon A. Jacobson, John F. Randolph, Siobàn D. Harlow
Motivated by the study of the longitudinal development and
progression of knee osteoarthritis (OA) over a 15-year period,
this study developed non-parametric mixed-effect models for
ordinal outcomes. A stochastic mixed-effect model was used to
evaluate the similarity of trajectories associated with increasing
disease severity of OA in both knees. Then, a non-parametric
mixed-effects model, based on cubic B-splnes, was developed
to characterize the unknown nonlinear trend of logits as a
function of time1-order. A Markov Transition Model was
developed to characterize the transitions among multi-states of
knee OA. This newly developed approach allows more flexible
functional dependence of the ordinal outcome, levels of
increasing knee OA severity, on the covariates. Full Text
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