I am actively developing the R package "dtms". The package implements discrete-time multistate models in R. It comes with many tools to analyze the results of multistate models. The workflow mainly consists of estimating a discrete-time multistate model and then applying methods for absorbing Markov chains. The package comes with features for data handling and editing, several methods for estimating transition probabilities, an extensive set of Markov chain methods, and further analytical tools and methods. The most recent version of the package is available on GitHub:

https://github.com/christiandudel/dtms

I have made several methodological contributions to the literature on Markov chain methods. These contributions are described in the following papers:

Dudel, C., Schneider, D. (2023): How bad could it be? Worst-case bounds on bias in multistate models due to unobserved transitions. Sociological Methods & Research 52: 1816-1837. [Open access article] [Code]

Dudel, C. (2021): Expanding the Markov chain tool box: Distributions of occupation times and waiting times. Sociological Methods & Research 50: 401-428. [Article] [Preprint] [Code]

Dudel, C., Myrskylä, M. (2020): Estimating the number and length of episodes in disability using a Markov chain approach. Population Health Metrics 18: 15. [Open access article] [Code]

I have been teaching on multistate models for several years, both as part of the International Max Planck Research School for Population, Health and Data Science (IMPRS-PHDS) and in workshops at various institutions. If you are interested in hosting a workshop please get in touch. 

Forthcoming workshops:

Hertie School, Berlin, August 17, 2026. [More information]

Previous workshops:

Oslo Metropolitan University, January 6-7, 2026. [More information]

University of Helsinki, November 30-31, 2025. 

My applied work which uses multistate models to answer substantive questions includes the following papers: 

Abrams, L., Dudel, C., Feraldi, A. (2025): Who works while sick and who enjoys the golden years? Changing disparities in time spent in health and work after age 50 in the United States. Work, Aging and Retirement. [Open access article] [Code]  

Shi, J., Dudel, C., Monden, C., van Raalte, A. (2023): Inequalities in retirement lifespan in the United States. Journals of Gerontology, Series B 78: 891–901. [Open access article] [Preprint] [Code]

Höhn, A., McGurnaghan , S. J., Caparrotta, T. M., Jeyam, A., O'Reilly, J. E., Blackbourn, L. A. K., Hatam, S., Dudel, C., Seaman, R. J., Mellor, J., Sattar, N., McCrimmon, R. J., Kennon, B., Petrie, J. R., Wild, S., McKeigue, P. M., Colhoun, H. M. (2022): Large socioeconomic gap in period life expectancy and life years spent with complications of diabetes in the Scottish population with type 1 diabetes, 2013–2018. PLoS One 17(8): e0271110. [Open access article] 

Hale, J., Dudel, C., Lorenti, A. (2021): Cumulative disparities in the dynamics of working poverty for later-career U.S. workers (2002-2012). Socius 7. [Open access article] [Preprint] [Code]

Lorenti, A., Dudel, C., Hale, J., Myrskylä, M. (2020): Working and disability expectancies at older ages: the role of childhood circumstances and education. Social Science Research 91: 102447. [Open access article] [Preprint] [Code]

Lorenti, A., Dudel, C., Myrskylä, M. (2019): The legacy of the Great Recession in Italy: A wider geographical, gender, and generational gap in working life expectancy. Social Indicators Research 142: 283-303. [Open access article]

Dudel, C., López Gómez, M., Benavides, F., Myrskylä, M. (2018): The Length of Working Life in Spain: Levels, Recent Trends, and the Impact of the Financial Crisis. European Journal of Population 34: 769-791. [Open access article] [Preprint]

Dudel, C., Myrskylä, M. (2017): Working Life Expectancy at Age 50 in the US and the Impact of the Great Recession. Demography 54: 2101-2121. [Open access article] [Preprint] [Data] [Code]