@article{zhang_wu_denton_wilson_lobo_2019, title={Probabilistic sensitivity analysis on Markov models with uncertain transition probabilities: an application in evaluating treatment decisions for type 2 diabetes}, volume={22}, ISSN={1386-9620 1572-9389}, url={http://dx.doi.org/10.1007/S10729-017-9420-8}, DOI={10.1007/s10729-017-9420-8}, abstractNote={Markov models are commonly used for decision-making studies in many application domains; however, there are no widely adopted methods for performing sensitivity analysis on such models with uncertain transition probability matrices (TPMs). This article describes two simulation-based approaches for conducting probabilistic sensitivity analysis on a given discrete-time, finite-horizon, finite-state Markov model using TPMs that are sampled over a specified uncertainty set according to a relevant probability distribution. The first approach assumes no prior knowledge of the probability distribution, and each row of a TPM is independently sampled from the uniform distribution on the row's uncertainty set. The second approach involves random sampling from the (truncated) multivariate normal distribution of the TPM's maximum likelihood estimators for its rows subject to the condition that each row has nonnegative elements and sums to one. The two sampling methods are easily implemented and have reasonable computation times. A case study illustrates the application of these methods to a medical decision-making problem involving the evaluation of treatment guidelines for glycemic control of patients with type 2 diabetes, where natural variation in a patient's glycated hemoglobin (HbA1c) is modeled as a Markov chain, and the associated TPMs are subject to uncertainty.}, number={1}, journal={Health Care Management Science}, publisher={Springer Nature}, author={Zhang, Yuanhui and Wu, Haipeng and Denton, Brian T. and Wilson, James R. and Lobo, Jennifer M.}, year={2019}, month={Mar}, pages={34–52} }
 @article{mccoy_zhang_herrin_denton_mason_montori_smith_shah_2015, title={Changing trends in type 2 diabetes mellitus treatment intensification, 2002-2010}, volume={21}, number={5}, journal={American Journal of Managed Care}, author={McCoy, R. G. and Zhang, Y. H. and Herrin, J. and Denton, B. T. and Mason, J. E. and Montori, V. M. and Smith, S. A. and Shah, N. D.}, year={2015}, pages={E288-} }
 @article{zhang_mccoy_mason_smith_shah_denton_2014, title={Second- line agents for glycemic control for type 2 diabetes: Are newer agents better?}, volume={37}, number={5}, journal={Diabetes Care}, author={Zhang, Y. H. and McCoy, R. G. and Mason, J. E. and Smith, S. A. and Shah, N. D. and Denton, B. T.}, year={2014}, pages={1338–1345} }
 @misc{zhang_mccoy_mason_smith_shah_denton_2014, title={Second-line agents for glycemic control for type 2 diabetes: Are newer agents better? Diabetes care 2014;37:1338-1345 response}, volume={37}, number={9}, journal={Diabetes Care}, author={Zhang, Y. and McCoy, R. G. and Mason, J. E. and Smith, S. A. and Shah, N. D. and Denton, B. T.}, year={2014}, pages={E206–207} }