sjmisc: Data Transformation and Labelled Data Utility Functions

Collection of miscellaneous utility functions (especially intended for people coming from other statistical software packages like 'SPSS', and/ or who are new to R), supporting following common tasks when working with data : 1) Reading and writing data between R and other statistical software packages like 'SPSS', 'SAS' or 'Stata' and working with labelled data; this includes easy ways to get and set label attributes, to convert labelled vectors into factors (and vice versa), or to deal with multiple declared missing values etc. 2) Data transformation tasks like recoding, dichotomizing or grouping variables, setting and replacing missing values. The data transformation functions also support labelled data.

Version: 2.3.0
Depends: R (≥ 3.2), stats, utils
Imports: broom (≥ 0.4.1), dplyr (≥ 0.5.0), haven (≥ 1.0.0), psych, purrr, stringdist (≥ 0.9.4), stringr (≥ 1.1.0), tibble (≥ 1.2.0), tidyr (≥ 0.6.0)
Suggests: Hmisc, mice, sjPlot, sjstats (≥ 0.7.0), knitr, rmarkdown
Published: 2017-02-08
Author: Daniel Lüdecke
Maintainer: Daniel Lüdecke <d.luedecke at>
License: GPL-3
NeedsCompilation: no
Citation: sjmisc citation info
Materials: README NEWS
CRAN checks: sjmisc results


Reference manual: sjmisc.pdf
Vignettes: The Design Philosophy of Functions in sjmisc
Exploring Data Sets
Labelled Data and the sjmisc-Package
Working with Labelled Data
Package source: sjmisc_2.3.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Mavericks binaries: r-release: sjmisc_2.3.0.tgz, r-oldrel: sjmisc_2.3.0.tgz
Old sources: sjmisc archive

Reverse dependencies:

Reverse imports: miceadds, sjPlot, sjstats, tadaatoolbox


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