Stata to R Reference

This reference helps Stata users find an R implementation of a familiar operation. It accompanies tidystata, but covers base R and other packages wherever they offer a useful approach. It is a lookup companion, not a textbook.

The catalogue contains 514 command families and 1782 paired examples. Its 707 lookup keys also include Stata functions, operators and prefixes. The R index describes 948 function/package pairs. Abbreviations and alternative implementations do not inflate command-family counts.

Find your task

  • Use Command reference in the header; its sidebar lists every subject chapter.
  • Open the Stata index for a command you already know.
  • Open the R index to browse functions by package.
  • Search for a command, R function or task. Expand further examples when you need options or a different R approach.

Every chapter has a 中文 switch. It opens the same chapter and, when you follow an example link, the same example in Chinese.

Look it up in R

library(tidystata)
findit(tab)
findit(tab, sex, region)
findit("merge 1:1 id, keep(match)")
findit(dplyr::left_join)
findit("how do I remove duplicate rows")
findit(tab) |> print(n = Inf)

findit() and this book share one catalogue. Clear console queries show a preferred answer; expansion exposes the remaining examples. The lookup does not load or install the packages named in its results.

Adapt an example

data is your dataset; x, y, g, id and time are illustrative column names. data1 and data2 are two datasets, and fit is an existing fitted model. Some snippets need setup described in their task or qualification. A snippet is not necessarily a standalone analysis.

Code with package::function() identifies its package explicitly. The label beneath each example names its primary package; helpers may use other packages listed in the function index. Attach packages for unqualified calls as needed.

About the notes

A note tagged Differs from Stata means the R code does the same job, but a default, the missing-value handling, an estimator or the output layout differs; the note says how. Other notes are practical tips. Most R examples are run against checks when the catalogue is built; these test the R code itself, not numerical parity with Stata. Missing values, weights, reference levels and standard errors deserve particular attention when comparing results.

Keep learning

See the tidystata documentation for package help, and Minghong Shen’s website and books for longer learning material. Report missing or incorrect comparisons through the package issue tracker.