Paquetes usados

En la documentación y ejercicios de este workshop se usaron los paquetes que se pueden ver abajo. Este listado se creó automáticamente usando {grateful}:

grateful::cite_packages(pkgs = "All", output = "paragraph", out.format = "Rmd", include.RStudio = FALSE, out.dir = "../data/bib/")

We used R version 4.3.3 (R Core Team 2024) and the following R packages: afex v. 1.3.1 (Singmann et al. 2024), car v. 3.1.2 (Fox and Weisberg 2019), correlation v. 0.8.5 [@], corrplot v. 0.92 (Wei and Simko 2021), corrr v. 0.4.4 (Kuhn, Jackson, and Cimentada 2022), cowplot v. 1.1.3 (Wilke 2024a), DT v. 0.33 (Xie, Cheng, and Tan 2024), esquisse v. 2.0.0 (Meyer and Perrier 2024), gapminder v. 1.0.0 (Bryan 2023), geomtextpath v. 0.1.4 (Cameron and van den Brand 2024), gghighlight v. 0.4.1 (Yutani 2023), ggrain v. 0.0.4 (Allen et al. 2021), ggraph v. 2.2.1 (Pedersen 2024), ggridges v. 0.5.6 (Wilke 2024b), ggtext v. 0.1.2 (Wilke and Wiernik 2022), ggthemes v. 5.1.0 (Arnold 2024), gt v. 0.11.0 (Iannone et al. 2024), gtsummary v. 1.7.2 (Sjoberg et al. 2021), here v. 1.0.1 (Müller 2020), inspectdf v. 0.0.12 (Rushworth 2022), janitor v. 2.2.0 (Firke 2023), jsPsychHelpeR v. 0.3.5.903 (Navarrete 2024a), jsPsychMaker v. 0.3.5.901 (Navarrete and Valencia 2024), jsPsychMonkeys v. 0.3.5.901 (Navarrete 2024b), knitr v. 1.48 (Xie 2014, 2015, 2024a), lme4 v. 1.1.35.5 (Bates et al. 2015), pak v. 0.7.2 (Csárdi and Hester 2024), papaja v. 0.1.2 (Aust and Barth 2023), parameters v. 0.22.1 (Lüdecke et al. 2020), performance v. 0.12.2 (Lüdecke, Ben-Shachar, et al. 2021), plotly v. 4.10.4 (Sievert 2020), quarto v. 1.4.4 (Allaire and Dervieux 2024), RColorBrewer v. 1.1.3 (Neuwirth 2022), readODS v. 2.3.0 (Schutten et al. 2024), regexplain v. 0.2.2.9000 (Aden-Buie 2024), remotes v. 2.5.0 (Csárdi et al. 2024), renv v. 1.0.7 (Ushey and Wickham 2024), report v. 0.5.9 (Makowski et al. 2023), rmarkdown v. 2.27 (Xie, Allaire, and Grolemund 2018; Xie, Dervieux, and Riederer 2020; Allaire, Xie, Dervieux, McPherson, et al. 2024), rticles v. 0.27 (Allaire, Xie, Dervieux, R Foundation, et al. 2024), scales v. 1.3.0 (Wickham, Pedersen, and Seidel 2023), see v. 0.8.5 (Lüdecke, Patil, et al. 2021), sjPlot v. 2.8.16 (Lüdecke 2024), skimr v. 2.1.5 (Waring et al. 2022), stringi v. 1.8.4 (Gagolewski 2022), tidyverse v. 2.0.0 (Wickham et al. 2019), tinytex v. 0.52 (Xie 2019, 2024b), usethis v. 2.2.3 (Wickham et al. 2024), waldo v. 0.5.2 (Wickham 2023), writexl v. 1.5.0 (Ooms 2024).

References

Aden-Buie, Garrick. 2024. regexplain: Rstudio Addin to Explain, Test and Build Regular Expressions. https://github.com/gadenbuie/regexplain.
Allaire, JJ, and Christophe Dervieux. 2024. quarto: R Interface to “Quarto” Markdown Publishing System. https://github.com/quarto-dev/quarto-r.
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.
Allaire, JJ, Yihui Xie, Christophe Dervieux, R Foundation, Hadley Wickham, Journal of Statistical Software, Ramnath Vaidyanathan, et al. 2024. rticles: Article Formats for r Markdown. https://CRAN.R-project.org/package=rticles.
Allen, Micah, Davide Poggiali, Kirstie Whitaker, Tom Rhys Marshall, Jordy van Langen, and Rogier A. Kievit. 2021. “Raincloud Plots: A Multi-Platform Tool for Robust Data Visualization [Version 2; Peer Review: 2 Approved].” Wellcome Open Research 4 (63). https://doi.org/10.12688/wellcomeopenres.15191.2.
Arnold, Jeffrey B. 2024. ggthemes: Extra Themes, Scales and Geoms for “ggplot2”. https://CRAN.R-project.org/package=ggthemes.
Aust, Frederik, and Marius Barth. 2023. papaja: Prepare Reproducible APA Journal Articles with R Markdown. https://github.com/crsh/papaja.
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.
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Cameron, Allan, and Teun van den Brand. 2024. geomtextpath: Curved Text in “ggplot2”. https://allancameron.github.io/geomtextpath/.
Csárdi, Gábor, and Jim Hester. 2024. pak: Another Approach to Package Installation. https://pak.r-lib.org/.
Csárdi, Gábor, Jim Hester, Hadley Wickham, Winston Chang, Martin Morgan, and Dan Tenenbaum. 2024. remotes: R Package Installation from Remote Repositories, Including “GitHub”. https://remotes.r-lib.org.
Firke, Sam. 2023. janitor: Simple Tools for Examining and Cleaning Dirty Data. https://github.com/sfirke/janitor.
Fox, John, and Sanford Weisberg. 2019. An R Companion to Applied Regression. Third. Thousand Oaks CA: Sage. https://socialsciences.mcmaster.ca/jfox/Books/Companion/.
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Kuhn, Max, Simon Jackson, and Jorge Cimentada. 2022. corrr: Correlations in r. https://CRAN.R-project.org/package=corrr.
Lüdecke, Daniel. 2024. sjPlot: Data Visualization for Statistics in Social Science. https://CRAN.R-project.org/package=sjPlot.
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Lüdecke, Daniel, Indrajeet Patil, Mattan S. Ben-Shachar, Brenton M. Wiernik, Philip Waggoner, and Dominique Makowski. 2021. “see: An R Package for Visualizing Statistical Models.” Journal of Open Source Software 6 (64): 3393. https://doi.org/10.21105/joss.03393.
Makowski, Dominique, Daniel Lüdecke, Indrajeet Patil, Rémi Thériault, Mattan S. Ben-Shachar, and Brenton M. Wiernik. 2023. “Automated Results Reporting as a Practical Tool to Improve Reproducibility and Methodological Best Practices Adoption.” CRAN. https://easystats.github.io/report/.
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Müller, Kirill. 2020. here: A Simpler Way to Find Your Files. https://CRAN.R-project.org/package=here.
Navarrete, Gorka. 2024a. jsPsychHelpeR: Standardize and Automatize Data Preparation and Analysis of jsPsych Experiments Created with jsPsychMaker. https://github.com/gorkang/jsPsychHelpeR.
———. 2024b. jsPsychMonkeys: Release Monkeys to a jsPsych Experiment Using the r Package targets, Docker and RSelenium. https://github.com/gorkang/jsPsychMonkeys.
Navarrete, Gorka, and Herman Valencia. 2024. jsPsychMaker: Create Behavioral Experiments and Surveys Using jsPsych and r. https://github.com/gorkang/jsPsychMaker.
Neuwirth, Erich. 2022. RColorBrewer: ColorBrewer Palettes.
Ooms, Jeroen. 2024. writexl: Export Data Frames to Excel “xlsx” Format. https://CRAN.R-project.org/package=writexl.
Pedersen, Thomas Lin. 2024. ggraph: An Implementation of Grammar of Graphics for Graphs and Networks. https://CRAN.R-project.org/package=ggraph.
R Core Team. 2024. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.
Rushworth, Alastair. 2022. inspectdf: Inspection, Comparison and Visualisation of Data Frames. https://CRAN.R-project.org/package=inspectdf.
Schutten, Gerrit-Jan, Chung-hong Chan, Peter Brohan, Detlef Steuer, and Thomas J. Leeper. 2024. readODS: Read and Write ODS Files. https://docs.ropensci.org/readODS/.
Sievert, Carson. 2020. Interactive Web-Based Data Visualization with r, Plotly, and Shiny. Chapman; Hall/CRC. https://plotly-r.com.
Singmann, Henrik, Ben Bolker, Jake Westfall, Frederik Aust, and Mattan S. Ben-Shachar. 2024. afex: Analysis of Factorial Experiments. https://afex.singmann.science/.
Sjoberg, Daniel D., Karissa Whiting, Michael Curry, Jessica A. Lavery, and Joseph Larmarange. 2021. “Reproducible Summary Tables with the Gtsummary Package.” The R Journal 13: 570–80. https://doi.org/10.32614/RJ-2021-053.
Ushey, Kevin, and Hadley Wickham. 2024. renv: Project Environments. https://CRAN.R-project.org/package=renv.
Waring, Elin, Michael Quinn, Amelia McNamara, Eduardo Arino de la Rubia, Hao Zhu, and Shannon Ellis. 2022. skimr: Compact and Flexible Summaries of Data. https://docs.ropensci.org/skimr/ (website).
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Wickham, Hadley. 2023. waldo: Find Differences Between r Objects. https://waldo.r-lib.org.
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Wickham, Hadley, Thomas Lin Pedersen, and Dana Seidel. 2023. scales: Scale Functions for Visualization. https://scales.r-lib.org.
Wilke, Claus O. 2024a. cowplot: Streamlined Plot Theme and Plot Annotations for “ggplot2”. https://CRAN.R-project.org/package=cowplot.
———. 2024b. ggridges: Ridgeline Plots in “ggplot2”. https://CRAN.R-project.org/package=ggridges.
Wilke, Claus O., and Brenton M. Wiernik. 2022. ggtext: Improved Text Rendering Support for “ggplot2”. https://wilkelab.org/ggtext/.
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———. 2015. Dynamic Documents with R and Knitr. 2nd ed. Boca Raton, Florida: Chapman; Hall/CRC. https://yihui.org/knitr/.
———. 2019. “TinyTeX: A Lightweight, Cross-Platform, and Easy-to-Maintain LaTeX Distribution Based on TeX Live.” TUGboat 40 (1): 30–32. https://tug.org/TUGboat/Contents/contents40-1.html.
———. 2024a. knitr: A General-Purpose Package for Dynamic Report Generation in r. https://yihui.org/knitr/.
———. 2024b. tinytex: Helper Functions to Install and Maintain TeX Live, and Compile LaTeX Documents. https://github.com/rstudio/tinytex.
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Xie, Yihui, Joe Cheng, and Xianying Tan. 2024. DT: A Wrapper of the JavaScript Library “DataTables”. https://CRAN.R-project.org/package=DT.
Xie, Yihui, Christophe Dervieux, and Emily Riederer. 2020. R Markdown Cookbook. Boca Raton, Florida: Chapman; Hall/CRC. https://bookdown.org/yihui/rmarkdown-cookbook.
Yutani, Hiroaki. 2023. gghighlight: Highlight Lines and Points in “ggplot2”. https://CRAN.R-project.org/package=gghighlight.