Freedom251 › Statistical Analysis Software
sjmisc
What sjmisc is
sjmisc is a free GPL-3 R package for preparing data and transforming variables. It complements dplyr and works with tidyverse packages in pipes or with mutate(). Functions can recode and dichotomize values, group variables, and set or replace missing values. The package supports labelled data, including data imported from SPSS or Stata. Additional tools cover standardizing and centering variables, reshaping data, handling missing values, and descriptive statistics. Transformation functions accept either a vector or data frame first and return the same type of object. The stable release installs from CRAN with install.packages("sjmisc"), while a development snapshot is available from GitHub through devtools. CRAN lists R version 3.4 or later as a dependency. sjmisc runs on Linux, macOS, and Windows as a desktop package, and the project names Daniel Lüdecke as author and maintainer.
Who it suits
sjmisc suits researchers preparing datasets, especially when working with labelled variables from other statistical software. It is also useful for R users already using dplyr and tidyverse pipelines.
What it does well
- Free GPL-3 licensed R package
- Supports labelled SPSS and Stata data
- Works with dplyr and tidyverse pipes
- Handles recoding and missing values
- Available through CRAN or GitHub
What to know first
- Requires R version 3.4 or later
- Provides no statistical tests
- Provides no regression models
- Provides no Bayesian analysis
Plans
| Plan | Billed and limits | Price |
|---|---|---|
| sjmisc | GPL-3 licensed R package | Free |
As strengejacke.github.io lists them, read 11 Oct 2026. The maker's own page has the final word.
Verdict
sjmisc focuses on practical data preparation rather than statistical modeling. Its labelled-data support and tidyverse-compatible transformations make it a focused utility package for R workflows.
Facts from sjmisc's own pages
- Additional functions
- The reference lists tools for standardizing and centering variables, handling missing values, reshaping data, and descriptive statistics. · strengejacke.github.io, 11 Oct 2026
- Bayesian analysis
- No · strengejacke.github.io, 23 Sept 2026
- Data tasks
- Its functions handle recoding, dichotomizing, grouping variables, and setting or replacing missing values. · strengejacke.github.io, 11 Oct 2026
- Deployment
- desktop · strengejacke.github.io, 23 Sept 2026
- Free plan
- Yes · strengejacke.github.io, 23 Sept 2026
- Function inputs
- The design guide says transformation functions can take a vector or data frame as their first argument and return an object of the same type. · strengejacke.github.io, 11 Oct 2026
- Install options
- The stable release installs from CRAN with install.packages("sjmisc"), and a development snapshot installs from GitHub using devtools. · strengejacke.github.io, 11 Oct 2026
- Intended users
- The project describes the package as addressing data-preparation needs in research, especially for users working with labelled data from other statistical software. · strengejacke.github.io, 11 Oct 2026
- Labelled data
- The package supports labelled data, including data often imported from SPSS or Stata. · strengejacke.github.io, 11 Oct 2026
- License
- The project site identifies GPL-3 as its license. · strengejacke.github.io, 11 Oct 2026
- Maintainer
- The project identifies Daniel Lüdecke as author and maintainer. · strengejacke.github.io, 11 Oct 2026
- Platforms
- CRAN lists Windows and macOS binaries, and provides a source package for installation on other supported R environments. · cloud.r-project.org, 11 Oct 2026
- Purpose
- sjmisc provides R utility functions for data and variable transformation, complementing dplyr. · strengejacke.github.io, 11 Oct 2026
- Regression models
- No · strengejacke.github.io, 23 Sept 2026
- Requirements
- CRAN lists R version 3.4 or later as a dependency. · cloud.r-project.org, 11 Oct 2026
- Scripting support
- Yes · strengejacke.github.io, 23 Sept 2026
- Statistical tests
- No · strengejacke.github.io, 23 Sept 2026
- Support
- The project site links to GitHub for bug reports and source code. · strengejacke.github.io, 11 Oct 2026
- Tidyverse integration
- Its functions are designed to work with tidyverse packages such as dplyr and can be used in pipes or with mutate(). · strengejacke.github.io, 11 Oct 2026
Where sjmisc stands on Freedom251
- Statistical Analysis Software#38 of 106