Key Papers

• Islan et al which covers irregular timings; see also azz94log that covers this for the binary Y case
• Bayesian model

Lee - Daniels Marginalized Transition Model

• Mike Daniels Code: https://github.com/mjdaniels/Short_Course/blob/master/Transition
• Papers citing lee07cla:
  1. Keunbaik Lee and Yongsung Joo, Marginalized models for longitudinal count data, Computational Statistics & Data Analysis, 10.1016/j.csda.2019.01.001, (2019).
  2. Subrata Rana, Surupa Roy and Kalyan Das, Analysis of ordinal longitudinal data under nonignorable missingness and misreporting: An application to Alzheimer’s disease study, Journal of Multivariate Analysis, 10.1016/j.jmva.2018.02.004, 166, (62-77), (2018).
  3. Idemauro Antonio Rodrigues de Lara, John Hinde and Cesar Augusto Taconeli, An alternative method for evaluating stationarity in transition models, Journal of Statistical Computation and Simulation, 10.1080/00949655.2017.1351562, 87, 15, (2962-2980), (2017).
  4. Keunbaik Lee, Insuk Sohn and Donguk Kim, Analysis of long series of longitudinal ordinal data using marginalized models, Computational Statistics & Data Analysis, 10.1016/j.csda.2015.07.010, 94, (363-371), (2016).
  5. S. Mahmoud Taheri, Fatemeh Salmani, Alireza Abadi and Hamid Alavi Majd, A transition model for fuzzy correlated longitudinal responses, Journal of Intelligent & Fuzzy Systems, 10.3233/IFS-152040, 30, 3, (1265-1273), (2016).
  6. Joo Yeong Jeon and Keunbaik Lee, Review and discussion of marginalized random effects models, Journal of the Korean Data and Information Science Society, 10.7465/jkdi.2014.25.6.1263, 25, 6, (1263-1272), (2014).
  7. Keunbaik Lee and Sunah Sung, Autoregressive Cholesky Factor Modeling for Marginalized Random Effects Models, Communications for Statistical Applications and Methods, 10.5351/CSAM.2014.21.2.169, 21, 2, (169-181), (2014).
  8. Mojtaba Ganjali, Taban Baghfalaki and Zahra R. Ghahrodi, Transitional Ordinal Modeling, Wiley StatsRef: Statistics Reference Online, (1-13), (2017).
  9. Myungok Lee, Keunbaik Lee and JungBok Lee, Marginalized transition shared random effects models for longitudinal binary data with nonignorable dropout, Biometrical Journal, 56, 2, (230-242), (2014).
  10. Kyeongmi Cheon, Marie E. Thoma, Xiangrong Kong and Paul S. Albert, A mixture of transition models for heterogeneous longitudinal ordinal data: with applications to longitudinal bacterial vaginosis data, Statistics in Medicine, 33, 18, (3204-3213), (2014).
  11. K. Lee, M. J. Daniels and Y. Joo, Flexible marginalized models for bivariate longitudinal ordinal data, Biostatistics, 10.1093/biostatistics/kxs058, 14, 3, (462-476), (2013).
  12. Yunlong Xie and Dale L. Zimmerman, Antedependence models for nonstationary categorical longitudinal data with ignorable missingness: likelihood‐based inference, Statistics in Medicine, 32, 19, (3274-3289), (2013).
  13. Keunbaik Lee and Michael J. Daniels, Causal inference for bivariate longitudinal quality of life data in presence of death by using global odds ratios, Statistics in Medicine, 32, 24, (4275-4284), (2013).
  14. Bibliography, Analysis of Ordinal Categorical Data, (359-388), (2012).
  15. Keunbaik Lee, Sanggil Kang, Xuefeng Liu and Daekwan Seo, Likelihood-based approach for analysis of longitudinal nominal data using marginalized random effects models, Journal of Applied Statistics, 10.1080/02664763.2010.515675, 38, 8, (1577-1590), (2010).
  16. Keunbaik Lee and Donald Mercante, Longitudinal nominal data analysis using marginalized models, Computational Statistics & Data Analysis, 10.1016/j.csda.2009.08.005, 54, 1, (208-218), (2010).
  17. Kuo-Chin Lin, Goodness-of-fit tests for modeling longitudinal ordinal data, Computational Statistics & Data Analysis, 10.1016/j.csda.2010.02.013, 54, 7, (1872-1880), (2010).
  18. C. Varin and C. Czado, A mixed autoregressive probit model for ordinal longitudinal data, Biostatistics, 10.1093/biostatistics/kxp042, 11, 1, (127-138), (2009).
  19. Baojiang Chen, Grace Y. Yi and Richard J. Cook, Likelihood analysis of joint marginal and conditional models for longitudinal categorical data, Canadian Journal of Statistics, 37, 2, (182-205), (2009).
  20. Keunbaik Lee, Yongsung Joo, Jae Keun Yoo and JungBok Lee, Marginalized random effects models for multivariate longitudinal binary data, Statistics in Medicine, 28, 8, (1284-1300), (2009).
  21. Euijung Ryu, Simultaneous confidence intervals using ordinal effect measures for ordered categorical outcomes, Statistics in Medicine, 28, 25, (3179-3188), (2009).
  22. Keunbaik Lee and Michael J. Daniels, Marginalized models for longitudinal ordinal data with application to quality of life studies, Statistics in Medicine, 27, 21, (4359-4380), (2008).
  23. Wei Liu, Bo Zhang, Zhiwei Zhang and Xiao-Hua Zhou, Joint Modeling of Transitional Patterns of Alzheimer’s Disease, PLoS ONE, 10.1371/journal.pone.0075487, 8, 9, (e75487), (2013).