---
title: "Development Roadmap"
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  eval = FALSE
)
```

This article outlines planned features for future versions of `summata`, informed by capabilities available in related packages and user feedback. The roadmap is tentative and subject to change based on development priorities and community input.

---

# Planned Features

The following features are under consideration for future releases, organized by priority level.

## Higher Priority

Features expected in near-term releases:

| Feature | Description | Reference |
|:--------|:------------|:----------|
| Paired/longitudinal tables | Summary tables for paired measurements across time points | `arsenal` |
| Subgroup analysis | Stratified analyses with syntax similar to `tbl_strata()` | `gtsummary` |
| Missing data visualization | Visual patterns of missingness for data quality assessment | `finalfit` |

## Medium Priority

Features planned for subsequent releases:

| Feature | Description | Reference |
|:--------|:------------|:----------|
| Inline text reporting | Extract statistics for R Markdown inline reporting | `gtsummary` |
| Survey-weighted analysis | Support for `svyglm()`, `svycoxph()` from the survey package | `gtsummary`, `survey` |
| Competing risks regression | Fine-Gray models via the `cmprsk` package | `finalfit` |
| Multinomial regression | Support for `nnet::multinom()` with multi-level categorical outcomes | `gtsummary`, `nnet` |
| Ordinal regression | Support for `MASS::polr()` and `ordinal::clm()` for ordered categorical outcomes | `MASS`, `ordinal` |
| Custom statistics | User-defined summary statistics functions for `desctable()` | `gtsummary` |

## Lower Priority

Features under consideration for future releases:

| Feature | Description | Reference |
|:--------|:------------|:----------|
| Bootstrap CIs | Bootstrapped confidence intervals for model predictions | `finalfit` |
| GAM models | Generalized additive model support via `mgcv` | `gtsummary` |
| Bayesian models | Support for `brmsfit` and `stanreg` model objects | `gtsummary` |

---

# Contributing

Contributions to `summata` are welcome. If interested in implementing a roadmap feature or proposing a new one, please consult the contributing guidelines in the [package repository](https://codeberg.org/phmcc/summata).

## Bug Reports

Bug reports and feature requests may be submitted via the issue tracker, either on [Codeberg](https://codeberg.org/phmcc/summata/issues) or [GitHub](https://github.com/phmcc/summata/issues).

## Development Repository

- **Primary development**: [codeberg.org/phmcc/summata](https://codeberg.org/phmcc/summata)
- **GitHub mirror**: [github.com/phmcc/summata](https://github.com/phmcc/summata)

---

# Version History

See the [Changelog](news/index.html) for a detailed history of changes in each release.

---

# Additional Resources

- [Feature Comparison](feature_comparison.html): Comparison with related packages
- [Benchmarks](benchmarks.html): Performance comparisons
- [gtsummary documentation](https://www.danieldsjoberg.com/gtsummary/)
- [finalfit documentation](https://finalfit.org/)
- [arsenal documentation](https://mayoverse.github.io/arsenal/)
