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A semi-parametric shared parameter model to handle nonmonotone nonignorable missingness. (English) Zbl 1159.62083
Summary: Longitudinal studies often generate incomplete response patterns according to a missing not at random mechanism. Shared parameter models provide an appealing framework for the joint modelling of the measurement and missingness processes, especially in the nonmonotone missingness case, and assume a set of random effects to induce the interdependence. Parametric assumptions are typically made for the random effects distribution, violation of which leads to model misspecification with a potential effect on the parameter estimates and standard errors.
We avoid any parametric assumption for the random effects distribution and leave it completely unspecified. The estimation of the model is then made using a semi-parametric maximum likelihood method. Our proposal is illustrated on a randomized longitudinal study on patients with rheumatoid arthritis exhibiting nonmonotone missingness.

62P10 Applications of statistics to biology and medical sciences; meta analysis
62G05 Nonparametric estimation
62N02 Estimation in survival analysis and censored data
Full Text: DOI
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