R

Switching from SPSS

Your data: Install the haven package, then read_sav() loads your SPSS data into R with value labels and special missing values kept. write_sav() saves back to .sav.

1. Install haven: In R, run install.packages("haven"), or install.packages("tidyverse") to get haven with the rest of the tidyverse.
2. Load it: Run library(haven).
3. Read your SPSS file: df <- read_sav("yourfile.sav") reads a .sav file. For older portable files, use read_por("yourfile.por").
4. Work with value labels: Labelled values come in as haven's labelled() class, so the original labels aren't lost. Use as_factor() to turn them into factors. Special missing values are preserved.
5. Save back to SPSS if you need to: write_sav(df, "out.sav") writes a .sav file that colleagues can open in SPSS.

Watch out for:

• Dates and times are converted to R date/time classes, and character vectors are not converted to factors.
• haven also reads Stata .dta (up to version 15) and SAS files, if you're moving from those too.

Full step-by-step guide →

Sources: haven.tidyverse.org, checked 19 Oct 2026.

Switching from Stata

Your data: Stata data files: .dta. R opens .dta, according to its own documentation.

1. Keep your data from Stata as a .dta file.
2. Open that file in R.

Watch out for:

• With the haven package (part of the tidyverse): read_sav(), read_por(), read_sas(), read_xpt(), read_dta().

Sources: jasp-stats.org/faq · haven.tidyverse.org, checked 19 Oct 2026.

Switching from SAS

Your data: SAS data files: .sas7bdat, .sas7bcat, .xpt. R opens .sas7bdat and .xpt, according to its own documentation.

1. Keep your data from SAS as .sas7bdat (with .sas7bcat for formats) or .xpt transport files.
2. Open that file in R.

Watch out for:

• With the haven package (part of the tidyverse): read_sav(), read_por(), read_sas(), read_xpt(), read_dta().

Sources: jasp-stats.org/faq · haven.tidyverse.org, checked 19 Oct 2026.