Research Using the NACC Database


Non-homogeneous Markov process models for rate of conversion to MCI 

 
   Lead Investigator:    Rebecca Hubbard
   Institution      :    NACC
   E-Mail           :    azhou@u.washington.edu
   Proposal ID      :    43

Publications:
1 Chen, B and Zhou, A A Correlated Random Effects Model for Non-homogeneous Markov Process with Nonignorable Missingness 2013 Journal Article J Multivariate Analysis 117 13-Jan
PUBLISHED

2 Chen, B and Zhou, XH Non-homogeneous Markov process models with informative observations with an application to Alzheimer's disease 2011 Journal Article Biometrical J 53 444-463
PUBLISHED

3 Hubbard, R Identifying risk factors for conversion between normal cognition, MCI, and dementia using Markov processes 2008 Abstract Alzheimer's and Dementia 4 T675-676
PUBLISHED

4 Hubbard, R and Zhou, XH A non-homogeneous Markov process model for Alzheimer's disease progression 2008 Abstract Int Biometrics Society 159
PUBLISHED

5 Hubbard, RA and Zhou, A Modeling Risk Factors for Alzheimer's Disease Progression Using a Nonhomogeneous Markov Process 2008 Abstract Joint Statistical Meeting 193
PUBLISHED

6 Hubbard, RA and Zhou, XH A comparison of non-homogeneous Markov regression models with application to Alzheimer's disease progression 2011 Journal Article J Applied Stat 38 2313-2326
PUBLISHED

7 Koepsell, T and Monsell, S Testing the First-Order Markov Assumption in Homogeneous Markov Modeling of Transition Probabilities between Cognitive States 2011 Abstract Alzheimer's and Dementia 7 S351-352
PUBLISHED

Proposal Description: