@article{huang_stefanski_davidian_2009, title={Latent-Model Robustness in Joint Models for a Primary Endpoint and a Longitudinal Process}, volume={65}, ISSN={["1541-0420"]}, DOI={10.1111/j.1541-0420.2008.01171.x}, abstractNote={Summary Joint modeling of a primary response and a longitudinal process via shared random effects is widely used in many areas of application. Likelihood‐based inference on joint models requires model specification of the random effects. Inappropriate model specification of random effects can compromise inference. We present methods to diagnose random effect model misspecification of the type that leads to biased inference on joint models. The methods are illustrated via application to simulated data, and by application to data from a study of bone mineral density in perimenopausal women and data from an HIV clinical trial.}, number={3}, journal={BIOMETRICS}, author={Huang, Xianzheng and Stefanski, Leonard A. and Davidian, Marie}, year={2009}, month={Sep}, pages={719–727} }
 @article{huang_stefanski_davidian_2006, title={Latent-model robustness in structural measurement error models}, volume={93}, ISSN={["1464-3510"]}, DOI={10.1093/biomet/93.1.53}, abstractNote={We present methods for diagnosing the effects of model misspecification of the true-predictor distribution in structural measurement error models. We first formulate latent-model robustness theoretically. Then we provide practical techniques for examining the adequacy of an assumed latent predictor model. The methods are illustrated via analytical examples, application to simulated data and with data from a study of coronary heart disease. Copyright 2006, Oxford University Press.}, number={1}, journal={BIOMETRIKA}, author={Huang, XZ and Stefanski, LA and Davidian, M}, year={2006}, month={Mar}, pages={53–64} }