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pagetitle: Joint Models
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# Resources

In the following Y refers to a longitudinal varible and T is time to an event.

## Models

* [Rizopoulos Course](rizopoulosCourse2019.pdf)
* [Verbeke Tutorial](verbeke2016.pdf) including lack of ability to get marginal inferences when conditioning one outcome distribution on the other outcome; nice layout of competing approaches with pros and cons
* [Semiparametric joint model in end-of-life studies](https://arxiv.org/pdf/1603.01851v2.pdf)
* [Bayesian nonparametric approach](pau20joi.pdf)

### Complex Y
* [Mixture model for many zeros in Y](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3212950)
* [Two-part joint model with bianry Y and excess zeros](riz08two.pdf)
* [Zero-inflated count data](https://journals.sagepub.com/doi/10.1177/0962280216659312)
* [Pattern mixture approach](https://repository.upenn.edu/dissertations/AAI3485714)
* [Multilevel Bayesian model with many zeros](https://amstat.tandfonline.com/doi/10.1080/01621459.2012.664517)

### Binary Y
* [Tutorial](https://www.r-bloggers.com/joint-models-with-categorical-longitudinal-outcomes) (original post [here](https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-018-0592-9))
* [Joint frailty model for recurrent events and death](ron06joi.pdf)
* [Joint modeling of binary response and survival data](https://phs.queensu.ca/source/Student%20Profiles/Jia%20Wang%20-%20PRACTICUM%20REPORT%20(final%20version).pdf)

### Applications
* [Huntington's Disease](https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-018-0592-9)

## Simulating Data
* [simsurv package](https://cran.r-project.org/web/packages/simsurv/vignettes/simsurv_usage.html)
* [simjoint](https://www.rdocumentation.org/packages/joineR/versions/1.2.5/topics/simjoint)