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First crack at table
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@jacob-long
jacob-long committed Aug 9, 2024
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Expand Up @@ -11,7 +11,7 @@ authors:
affiliations:
- name: School of Journalism and Mass Communications, University of South Carolina, USA
index: 1
date: 6 January 2024
date: 9 August 2024
bibliography: paper.bib

---
Expand Down Expand Up @@ -101,4 +101,19 @@ Finally, @spalti2023 use `weights_tests()` to
assess the sensitivity of their estimates to the influence of survey sampling
weights in their research on scientific misperceptions.

\newpage
\begin{landscape}

| **Feature** | `jtools` | `marginaleffects` | `modelsummary` | `sjPlot` | `ggeffects` | `gtsummary` | `performance` | `parameters` |
|------------------------------|--------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------|-----------------------------------------------------------------------|------------------------------------------------------------------------------------|-------------------------------------------------------------|---------------------------|--------------------------------------------------|
| **Model information** | Flexible summaries, robust SEs, VIFs, centered and scaled variables, model fit statistics | Marginal effects, contrasts, equivalence tests | All information available via `broom` and `parameters`, plus robust Ses | Flexible summaries, robust SEs, scaled variables, model fit statistics | Marginal effects, contrasts, equivalence tests (from `marginaleffects` or `emmeans`) | Information available via `broom`, pairwise comparisons | Model fit and diagnostics | Coefficient estimates, intervals, test statistics |
| **Supported models** | lm, glm, mixed models, survey data for summaries, many more for visualization | Over 100 types | All models supported by `broom` and `parameters` | lm, glm, mixed models, Bayesian models | Large number of models | All that are supported by `broom` | Large number of models | Large number, including structural models |
| **Visualization** | Effect plots, coefficient plots (`ggplot2`) | Visualization of marginal effects, similar to `ggeffects` | Coefficient plots (`ggplot2`) | Coefficient plots (`ggplot2`) | Plots for effects, predictions, etc. | Experimental coefficient plot functions | Uses `see` package | Visualization of model parameters |
| **Model summary export options** | Coefficient plots, tables to PDF/html/Word via "huxtable" | Limited (console-focused) | Most extensive, customizable, easy to use (Markdown, LaTeX, HTML, etc.) | To HTML | To HTML and Markdown | Extensive (Word, PDF, HTML, etc.) | To Markdown | To HTML and Markdown |
| **Interface** | User-friendly, non-standard evaluation, customizable, bundled features in single function calls | Simple, tidy, pipeline-oriented | Simple, user-friendly, power user features | User-friendly, easy to integrate | Simple, user-friendly, pipeline-oriented | Pipeline-oriented, focus on table output | User-friendly, simple | User-friendly |
| **Unique features** | Extensive survey/weights support, plot intervals with robust errors, include partial residuals on plots | Detailed marginal effect analysis, flexible contrasts and hypothesis testing, extensive documentation | Also includes summaries of data frames | Support for psychometric item analysis | Plot intervals with robust errors, plot partial residuals on plots | Medical research-oriented summaries, focus on data summaries | nan | Includes variable selection/data reduction tools |

\end{landscape}
\newpage

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