Upload a Stata .do, JAMOVI .omv, JASP .jasp, or SPSS .sps file and get back an .Rmd + knitted HTML report you can read, edit, and re-run. Built for replication research and transparent open science.
Why this exists
A lot of published analyses live inside proprietary or point-and-click tools. Re-running them, auditing them, or pulling a workflow into a teaching example often means rewriting the analysis from scratch in R. 2Rmarkdown gives you a starting R Markdown document that mirrors the original analysis, so you can read it, knit it, modify it, and share it with collaborators.
What it covers
Each format has its own converter, tuned to that ecosystem's quirks. Every converter produces the same kind of artifact: an.Rmdplus a knitted HTML report, with the original syntax preserved as comments.
Deterministic converter for Stata .do syntax files. Parses 53+ commands, expands macros (local, global, foreach, forvalues), handles factor variables and clustered/robust SE, and generates self-contained R Markdown reports targeting the fixest + modelsummary + tidyverse ecosystem.
✓53+ Stata commands with dedicated converters
✓95.9% command coverage across 237 real .do files
✓715+ automated tests, all passing
Extracts data and analysis configurations from JAMOVI .omv files, reconstructs the jmv R package function calls, and generates formatted R Markdown documents with all original analyses preserved. Supports descriptives, t-tests, ANOVA, correlation, regression, reliability, factor analysis, and more.
✓20+ jmv analysis functions supported
✓315 automated tests across 13 OMV files
✓Incomplete analysis filtering (skips empty formulas)
Extracts data and analysis configurations from .jasp archives (ZIP files containing SQLite databases and JSON metadata), maps them to equivalent R code using 80+ function mappings across 17 JASP packages, and generates formatted R Markdown documents. Covers frequentist and Bayesian analyses.
✓80+ function mappings across 17 JASP packages
✓Tested against 137+ .jasp files
✓Parse-only mode (avoids JASP package fragility)
Parses 30+ SPSS commands including full expression translation (17+ SPSS functions mapped to R equivalents), translates them to R code using the jmv package, and generates formatted R Markdown reports. Preserves variable labels and value labels from .sav files. Validated against GNU PSPP.
✓30+ SPSS analysis commands supported
✓17+ SPSS functions translated to R equivalents
✓246+ automated tests, all passing
How it works
Drop your source file (and the matching dataset, when the format needs one). The web UI auto-detects which converter to use.
The matching R package parses the syntax or analysis spec, maps it to equivalent R code (fixest, jmv, tidyverse, …), and assembles a self-contained R Markdown document.
The Rmd is knitted to HTML on the server. You download both files. The HTML contains the executed R code's actual output — not a copy of the source app's screen.
Open-source R packages
The web app is a convenience layer. Every converter is also a standalone R package you can install with remotes::install_github() and call from your own scripts or pipelines.
stata2rmarkdown
Source format: Stata
0 errors, 0 warnings, 0 notes
jamovi2rmarkdown
Source format: JAMOVI
0 errors, 0 warnings, 1 note
jasp2rmarkdown
Source format: JASP
0 errors, 0 warnings, 1 note
spss2rmarkdown
Source format: SPSS
0 errors, 0 warnings, 1 note
# install.packages("remotes")
remotes::install_github("giladfeldman/STATA2Rmarkdown")
remotes::install_github("giladfeldman/jamovi2rmarkdown")
remotes::install_github("giladfeldman/jasp2rmarkdown")
remotes::install_github("giladfeldman/spss2rmarkdown")All five packages (including the shared stat2rmarkdown core) are MIT licensed. Pull requests, bug reports, and additional test corpora are welcome.
What to expect
This is a working tool, not a finished product. The converters cover the analyses we've tested against real published scripts and replication corpora. Output is meant as a faithful starting point in R, not a guarantee of identical numerical results across every edge case. Always sanity-check the generated Rmd against the original analysis before relying on it.
Quotas & privacy
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