README.Rmd

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output: github_document
---

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knitr::opts_chunk$set(
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# {simswjm}: Simulating Stepped Wedge Trials With and Without Informative Dropout

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The {simswjm} package can be used to simulate data from stepped wedge trials with a continuous, binary, or count longitudinal outcome.
Moreover, data can be simulated assuming both non-informative and informative dropout, with the dropout mechanism according to a joint longitudinal-survival model with shared random effects or (loosely) based on a mixed effects logistic regression model.

This package is a companion to the manuscript titled "Analysis of cohort stepped wedge cluster-randomized trials with non-ignorable dropout via joint modeling", which is currently submitted for publication.
A pre-print is [available on arXiv](https://arxiv.org/abs/2404.14840).

# Installation

You can install the development version of {simswjm} from [GitHub](https://github.com/RedDoorAnalytics/simswjm) with:

``` r
# install.packages("remotes")
remotes::install_github("RedDoorAnalytics/simswjm")
```

# Example code

Example code to fit mixed-effects and joint models using the simulated data is included within this repository as well, in the [`testing/`](https://github.com/RedDoorAnalytics/simswjm/tree/main/testing) folder.
Specifically, models are fit using the `gsem` command in Stata for continuous, binary, count outcomes; more details in [this file](https://github.com/RedDoorAnalytics/simswjm/blob/main/testing/02-testanalysis.do).

# Citation

If you find this useful, please cite it in your work:

```{r}
citation("simswjm")
```

# Issues

If you have any questions or feedback on the package or experience any bugs, please [file an issue on GitHub](https://github.com/RedDoorAnalytics/simswjm/issues).