@article{copeland_vock_pieper_mark_palmer_2013, title={Impact of lung transplantation on recipient quality of life a serial, prospective, multicenter analysis through the first posttransplant year}, volume={143}, number={3}, journal={Chest}, author={Copeland, C. A. F. and Vock, D. M. and Pieper, K. and Mark, D. B. and Palmer, S. M.}, year={2013}, pages={744–750} }
 @article{vock_davidian_tsiatis_muir_2012, title={Mixed model analysis of censored longitudinal data with flexible random-effects density}, volume={13}, ISSN={["1468-4357"]}, DOI={10.1093/biostatistics/kxr026}, abstractNote={Mixed models are commonly used to represent longitudinal or repeated measures data. An additional complication arises when the response is censored, for example, due to limits of quantification of the assay used. While Gaussian random effects are routinely assumed, little work has characterized the consequences of misspecifying the random-effects distribution nor has a more flexible distribution been studied for censored longitudinal data. We show that, in general, maximum likelihood estimators will not be consistent when the random-effects density is misspecified, and the effect of misspecification is likely to be greatest when the true random-effects density deviates substantially from normality and the number of noncensored observations on each subject is small. We develop a mixed model framework for censored longitudinal data in which the random effects are represented by the flexible seminonparametric density and show how to obtain estimates in SAS procedure NLMIXED. Simulations show that this approach can lead to reduction in bias and increase in efficiency relative to assuming Gaussian random effects. The methods are demonstrated on data from a study of hepatitis C virus.}, number={1}, journal={BIOSTATISTICS}, author={Vock, David M. and Davidian, Marie and Tsiatis, Anastasios A. and Muir, Andrew J.}, year={2012}, month={Jan}, pages={61–73} }
 @article{vock_atchison_legler_mcclure_carlyle_jeavons_burton_2011, title={Accounting for model uncertainty in estimating global burden of disease}, volume={89}, number={2}, journal={Bulletin of the World Health Organization}, author={Vock, D. M. and Atchison, E. A. and Legler, J. M. and McClure, D. R. J. and Carlyle, J. C. and Jeavons, E. N. and Burton, A. H.}, year={2011}, pages={112–120} }