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JM: An R Package for the Joint Modelling of Longitudinal and Time-to-Event Data
Open accessAbstract
In longitudinal studies measurements are often collected on different types of outcomes for each subject. These may include several longitudinally measured responses (such as blood values relevant to the medical condition under study) and the time at which an event of particular interest occurs (e.g., death, development of a disease or dropout from the study). These outcomes are often separately analyzed; however, in many instances, a joint modeling approach is either required or may produce a better insight into the mechanisms that underlie the phenomenon under study. In this paper we present the R package JM that fits joint models for longitudinal and time-to-event data.
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Citations
Cites
Modeling Survival Data: Extending the Cox Model
Therneau, T. M., & Grambsch, P. M. (2000) · Statistics for Biology and Health · doi:10.1007/978-1-4757-3294-8 · Cited by 8,674
Linear Mixed Models for Longitudinal Data
Verbeke, G. (1997) · Lecture Notes in Statistics · doi:10.1007/978-1-4612-2294-1_3 · Cited by 3,506
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Rizopoulos, D. (2011) · Biometrics · doi:10.1111/j.1541-0420.2010.01546.x · Cited by 458
Self-citationGalazzo, G., van Best, N., Bervoets, L., Dapaah, I. O., Savelkoul, P. H., Hornef, M. W., Hutton, E. K., Morrison, K., Holloway, A. C., McDonald, H., et al. (2020) · Gastroenterology · doi:10.1053/j.gastro.2020.01.024 · Cited by 308
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Li, K., Chan, W., Doody, R. S., Quinn, J., Luo, S., & Initiative, T. A. D. N. (2017) · Journal of Alzheimer’s Disease · doi:10.3233/jad-161201 · Cited by 126
Metadata
- Authors
- Rizopoulos, D.
- Venue
- Journal of Statistical Software
- Publisher
- Foundation for Open Access Statistic
- Published
- 2010
- Volume
- 35
- Issue
- 9
- ISSN
- 1548-7660 (ISSN-L)
- OpenAlex
- W1846287826
- Cited by
- 486
- References
- 2
- FWCI
- 13.20
- Type
- journal article
- Language
- en
- Open access
- diamond
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- Rizopoulos, D. (2010). JM: An R Package for the Joint Modelling of Longitudinal and Time-to-Event Data. Journal of Statistical Software. https://doi.org/10.18637/jss.v035.i09
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