R packages used

Package Version Citation
base 4.4.3 R Core Team (2025)
broom.mixed 0.2.9.6 Bolker and Robinson (2024)
crew 1.2.0 Landau (2025)
faux 1.2.2 DeBruine (2025)
ggdist 3.3.3 Kay (2024); Kay (2025)
ggh4x 0.3.1 van den Brand (2025)
glmmTMB 1.1.11 Brooks et al. (2017); McGillycuddy et al. (2025)
glue 1.8.0 Hester and Bryan (2024)
here 1.0.1 Müller (2020)
insight 1.3.0 Lüdecke, Waggoner, and Makowski (2019)
knitr 1.50 Xie (2014); Xie (2015); Xie (2025)
lme4 1.1.37 Bates et al. (2015)
marginaleffects 0.27.0 Arel-Bundock, Greifer, and Heiss (2024)
metafor 4.8.0 Viechtbauer (2010)
patchwork 1.3.2 Pedersen (2025)
progressr 0.15.1 Bengtsson (2024)
renv 1.1.4 Ushey and Wickham (2025)
rmarkdown 2.29 Xie, Allaire, and Grolemund (2018); Xie, Dervieux, and Riederer (2020); Allaire et al. (2024)
scales 1.4.0 Wickham, Pedersen, and Seidel (2025)
tarchetypes 0.13.1 Landau (2021a)
targets 1.11.3 Landau (2021b)
tidyverse 2.0.0 Wickham et al. (2019)

You can paste this paragraph directly in your report:

We used R v. 4.4.3 (R Core Team 2025) and the following R packages: broom.mixed v. 0.2.9.6 (Bolker and Robinson 2024), crew v. 1.2.0 (Landau 2025), faux v. 1.2.2 (DeBruine 2025), ggdist v. 3.3.3 (Kay 2024, 2025), ggh4x v. 0.3.1 (van den Brand 2025), glmmTMB v. 1.1.11 (Brooks et al. 2017; McGillycuddy et al. 2025), glue v. 1.8.0 (Hester and Bryan 2024), here v. 1.0.1 (Müller 2020), insight v. 1.3.0 (Lüdecke, Waggoner, and Makowski 2019), knitr v. 1.50 (Xie 2014, 2015, 2025), lme4 v. 1.1.37 (Bates et al. 2015), marginaleffects v. 0.27.0 (Arel-Bundock, Greifer, and Heiss 2024), metafor v. 4.8.0 (Viechtbauer 2010), patchwork v. 1.3.2 (Pedersen 2025), progressr v. 0.15.1 (Bengtsson 2024), renv v. 1.1.4 (Ushey and Wickham 2025), rmarkdown v. 2.29 (Xie, Allaire, and Grolemund 2018; Xie, Dervieux, and Riederer 2020; Allaire et al. 2024), scales v. 1.4.0 (Wickham, Pedersen, and Seidel 2025), tarchetypes v. 0.13.1 (Landau 2021a), targets v. 1.11.3 (Landau 2021b), tidyverse v. 2.0.0 (Wickham et al. 2019).

Package citations

Allaire, JJ, Yihui Xie, Christophe Dervieux, Jonathan McPherson, Javier Luraschi, Kevin Ushey, Aron Atkins, et al. 2024. rmarkdown: Dynamic Documents for r. https://github.com/rstudio/rmarkdown.
Arel-Bundock, Vincent, Noah Greifer, and Andrew Heiss. 2024. “How to Interpret Statistical Models Using marginaleffects for R and Python.” Journal of Statistical Software 111 (9): 1–32. https://doi.org/10.18637/jss.v111.i09.
Bates, Douglas, Martin Mächler, Ben Bolker, and Steve Walker. 2015. “Fitting Linear Mixed-Effects Models Using lme4.” Journal of Statistical Software 67 (1): 1–48. https://doi.org/10.18637/jss.v067.i01.
Bengtsson, Henrik. 2024. progressr: An Inclusive, Unifying API for Progress Updates. https://CRAN.R-project.org/package=progressr.
Bolker, Ben, and David Robinson. 2024. broom.mixed: Tidying Methods for Mixed Models. https://CRAN.R-project.org/package=broom.mixed.
Brooks, Mollie E., Kasper Kristensen, Koen J. van Benthem, Arni Magnusson, Casper W. Berg, Anders Nielsen, Hans J. Skaug, Martin Maechler, and Benjamin M. Bolker. 2017. “glmmTMB Balances Speed and Flexibility Among Packages for Zero-Inflated Generalized Linear Mixed Modeling.” The R Journal 9 (2): 378–400. https://doi.org/10.32614/RJ-2017-066.
DeBruine, Lisa. 2025. faux: Simulation for Factorial Designs. Zenodo. https://doi.org/10.5281/zenodo.2669586.
Hester, Jim, and Jennifer Bryan. 2024. glue: Interpreted String Literals. https://CRAN.R-project.org/package=glue.
Kay, Matthew. 2024. “ggdist: Visualizations of Distributions and Uncertainty in the Grammar of Graphics.” IEEE Transactions on Visualization and Computer Graphics 30 (1): 414–24. https://doi.org/10.1109/TVCG.2023.3327195.
———. 2025. ggdist: Visualizations of Distributions and Uncertainty. https://doi.org/10.5281/zenodo.3879620.
Landau, William Michael. 2021a. tarchetypes: Archetypes for Targets.
———. 2021b. “The Targets r Package: A Dynamic Make-Like Function-Oriented Pipeline Toolkit for Reproducibility and High-Performance Computing.” Journal of Open Source Software 6 (57): 2959. https://doi.org/10.21105/joss.02959.
———. 2025. crew: A Distributed Worker Launcher Framework. https://CRAN.R-project.org/package=crew.
Lüdecke, Daniel, Philip Waggoner, and Dominique Makowski. 2019. “insight: A Unified Interface to Access Information from Model Objects in R.” Journal of Open Source Software 4 (38): 1412. https://doi.org/10.21105/joss.01412.
McGillycuddy, Maeve, David I. Warton, Gordana Popovic, and Benjamin M. Bolker. 2025. “Parsimoniously Fitting Large Multivariate Random Effects in glmmTMB.” Journal of Statistical Software 112 (1): 1–19. https://doi.org/10.18637/jss.v112.i01.
Müller, Kirill. 2020. here: A Simpler Way to Find Your Files. https://CRAN.R-project.org/package=here.
Pedersen, Thomas Lin. 2025. patchwork: The Composer of Plots. https://patchwork.data-imaginist.com.
R Core Team. 2025. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.
Ushey, Kevin, and Hadley Wickham. 2025. renv: Project Environments. https://CRAN.R-project.org/package=renv.
van den Brand, Teun. 2025. Ggh4x: Hacks for “ggplot2”. https://CRAN.R-project.org/package=ggh4x.
Viechtbauer, Wolfgang. 2010. “Conducting Meta-Analyses in R with the metafor Package.” Journal of Statistical Software 36 (3): 1–48. https://doi.org/10.18637/jss.v036.i03.
Wickham, Hadley, Mara Averick, Jennifer Bryan, Winston Chang, Lucy D’Agostino McGowan, Romain François, Garrett Grolemund, et al. 2019. “Welcome to the tidyverse.” Journal of Open Source Software 4 (43): 1686. https://doi.org/10.21105/joss.01686.
Wickham, Hadley, Thomas Lin Pedersen, and Dana Seidel. 2025. scales: Scale Functions for Visualization. https://CRAN.R-project.org/package=scales.
Xie, Yihui. 2014. “knitr: A Comprehensive Tool for Reproducible Research in R.” In Implementing Reproducible Computational Research, edited by Victoria Stodden, Friedrich Leisch, and Roger D. Peng. Chapman; Hall/CRC.
———. 2015. Dynamic Documents with R and Knitr. 2nd ed. Boca Raton, Florida: Chapman; Hall/CRC. https://yihui.org/knitr/.
———. 2025. knitr: A General-Purpose Package for Dynamic Report Generation in R. https://yihui.org/knitr/.
Xie, Yihui, J. J. Allaire, and Garrett Grolemund. 2018. R Markdown: The Definitive Guide. Boca Raton, Florida: Chapman; Hall/CRC. https://bookdown.org/yihui/rmarkdown.
Xie, Yihui, Christophe Dervieux, and Emily Riederer. 2020. R Markdown Cookbook. Boca Raton, Florida: Chapman; Hall/CRC. https://bookdown.org/yihui/rmarkdown-cookbook.