Test JOSS build action

.github/workflows/draft-pdf.yml

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+on: [push]
+
+jobs:
+  paper:
+    runs-on: ubuntu-latest
+    name: Paper Draft
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+      - name: Build draft PDF
+        uses: openjournals/openjournals-draft-action@master
+        with:
+          journal: joss
+          # This should be the path to the paper within your repo.
+          paper-path: paper.md
+      - name: Upload
+        uses: actions/upload-artifact@v1
+        with:
+          name: paper
+          # This is the output path where Pandoc will write the compiled
+          # PDF. Note, this should be the same directory as the input
+          # paper.md
+          path: paper.pdf

paper.bib

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+@Article{modelsummary,
+  title = {{modelsummary}: Data and Model Summaries in {R}},
+  author = {Vincent Arel-Bundock},
+  journal = {Journal of Statistical Software},
+  year = {2022},
+  volume = {103},
+  number = {1},
+  pages = {1--23},
+  doi = {10.18637/jss.v103.i01},
+}
+
+@Manual{sjPlot,
+  title = {sjPlot: Data Visualization for Statistics in Social Science},
+  author = {Daniel Lüdecke},
+  note = {R package version 2.8.15},
+  url = {https://CRAN.R-project.org/package=sjPlot},
+}
+
+@Article{see,
+  title = {{see}: An {R} Package for Visualizing Statistical Models},
+  author = {Daniel Lüdecke and Indrajeet Patil and Mattan S. Ben-Shachar and Brenton M. Wiernik and Philip Waggoner and Dominique Makowski},
+  journal = {Journal of Open Source Software},
+  year = {2021},
+  volume = {6},
+  number = {64},
+  pages = {3393},
+  doi = {10.21105/joss.03393},
+}
+
+@Book{car,
+    title = {An {R} Companion to Applied Regression},
+    edition = {Third},
+    author = {John Fox and Sanford Weisberg},
+    year = {2019},
+    publisher = {Sage},
+    address = {Thousand Oaks {CA}},
+    url = {https://socialsciences.mcmaster.ca/jfox/Books/Companion/},
+}
+
+@Article{sandwich,
+    title = {Various Versatile Variances: An Object-Oriented Implementation of Clustered Covariances in {R}},
+    author = {Achim Zeileis and Susanne K\"oll and Nathaniel Graham},
+    journal = {Journal of Statistical Software},
+    year = {2020},
+    volume = {95},
+    number = {1},
+    pages = {1--36},
+    doi = {10.18637/jss.v095.i01},
+}
+
+@Article{pbkrtest,
+    title = {A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models -- The {R} Package {pbkrtest}},
+    author = {Ulrich Halekoh and S{\o}ren H{\o}jsgaard},
+    journal = {Journal of Statistical Software},
+    year = {2014},
+    volume = {59},
+    number = {9},
+    pages = {1--30},
+    url = {http://www.jstatsoft.org/v59/i09/},
+}

paper.md

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+---
+title: 'jtools: Analysis and Presentation of Social Scientific Data'
+tags:
+  - R
+  - social science
+  - regression
+authors:
+  - name: Jacob A. Long
+    orcid: 0000-0002-1582-6214
+    affiliation: 1
+affiliations:
+ - name: School of Journalism and Mass Communications, University of South Carolina, USA
+   index: 1
+date: 26 October 2023
+bibliography: paper.bib
+
+---
+
+# Summary
+
+`jtools` is an R package designed to ease the exploration and
+presentation of regression models with a focus on the needs of social scientists.
+Most notably, it generates results summaries that are meant to provide some
+of the conveniences of commercial software such as Stata (e.g., calculating
+robust standard errors and integrating them into a results table).
+Additionally, `jtools` includes plotting functions to help users better 
+understand and share the results and predictions from fitted regression models.
+
+# Statement of need
+
+Among the users of R are working or trainee scientists who are accustomed to
+software that provides detailed and customizable summaries of regression results
+"out of the box" (i.e., integrated into the modules that fit the model). While
+R's `summary()` function provides useful information for many regression 
+models — such as the method provided for `lm()` including coefficients, 
+standard errors, test statistics, and *p*-values — there is typically little
+flexiblity for customizing the output. Generating results summaries with 
+additional information, such as robust standard errors, confidence intervals,
+transformed/centered variables, and variance inflation factors demands 
+considerably more programming knowledge and effort for the user, requiring more
+time and making mistakes more likely. These same concerns exist for the case of
+plotting predicted values from regression models.
+
+`jtools` provides an alternative to `summary()`, `summ()`, that allows users
+more flexibility in generating results tables for supported regression models.
+Importantly, these capabilities are accessible almost solely through
+arguments to `summ()`, thereby requiring little more programming knowledge
+than what is already required to fit a regression model and print a minimal 
+summary to the console. For plotting, the package includes `effect_plot()`
+for creating line plots for a focal predictor variable. Users may add 
+confidence intervals (including the ability to use robust standard errors for
+the plotted intervals), the observed data as plotted points, partial residuals
+as plotted points, and rug plots. Categorical predictors can be plotted as 
+bar charts of single points with error bars as well. Finally, `jtools` features
+the function `plot_coefs()` that allows users to plot regression coefficients
+with confidence intervals for one or more models. This is particularly useful
+for comparing nested/related model specifications. Plots are generated with 
+`ggplot2` — allowing knowledgeable users to further customize the appearance —
+but do not require the user to know how to use `ggplot2`.
+
+Other R packages exist to achieve some of these ends. In some cases, `jtools`
+is using third-party packages for computation and simply repackaging the results
+(e.g., `sandwich` [@sandwich] for robust standard errors and `pbkrtest` for computation of 
+*p*-values for multilevel models). `modelsummary` provides comparable
+functionality to `summ()` and has some advantages, such as a greater range
+of supported models and more support for exporting to external documents. 
+`marginaleffects`, `sjPlot`, and `see` offer support for plotting predicted 
+values from fitted regression models and again have some of their own 
+advantages, such as more supported model types. There is also overlap in 
+functionality with the `car` package (e.g., the computation of variance 
+inflation factors and partial residuals), although `jtools` aims to improve
+the user interface and support more model types in some cases.
+
+# Mathematics
+
+Single dollars ($) are required for inline mathematics e.g. $f(x) = e^{\pi/x}$
+
+Double dollars make self-standing equations:
+
+$$\Theta(x) = \left\{\begin{array}{l}
+0\textrm{ if } x < 0\cr
+1\textrm{ else}
+\end{array}\right.$$
+
+You can also use plain \LaTeX for equations
+\begin{equation}\label{eq:fourier}
+\hat f(\omega) = \int_{-\infty}^{\infty} f(x) e^{i\omega x} dx
+\end{equation}
+and refer to \autoref{eq:fourier} from text.
+
+# Citations
+
+Citations to entries in paper.bib should be in
+[rMarkdown](http://rmarkdown.rstudio.com/authoring_bibliographies_and_citations.html)
+format.
+
+If you want to cite a software repository URL (e.g. something on GitHub without a preferred
+citation) then you can do it with the example BibTeX entry below for @fidgit.
+
+For a quick reference, the following citation commands can be used:
+- `@author:2001`  ->  "Author et al. (2001)"
+- `[@author:2001]` -> "(Author et al., 2001)"
+- `[@author1:2001; @author2:2001]` -> "(Author1 et al., 2001; Author2 et al., 2002)"
+
+# Figures
+
+Figures can be included like this:
+![Caption for example figure.\label{fig:example}](figure.png)
+and referenced from text using \autoref{fig:example}.
+
+Figure sizes can be customized by adding an optional second parameter:
+![Caption for example figure.](figure.png){ width=20% }
+
+# Acknowledgements
+
+We acknowledge contributions from Brigitta Sipocz, Syrtis Major, and Semyeong
+Oh, and support from Kathryn Johnston during the genesis of this project.
+
+# References