sassy
The sassy package is a meta-package that aims to
make R easier for everyone, especially people with a background in SAS®.
The package brings several useful SAS® concepts to R, including data
libraries, formats and format catalogs, data dictionaries, a data step,
a traceable log, and a reporting package with a variety of printable
report types.
The core of the sassy system is the
procs package. This package contains replications of
several SAS® procedures: proc_freq(),
proc_means(), proc_ttest(),
proc_reg(), proc_transpose(), and
proc_sort(). Combined with the datastep()
function from the libr package, you can write code in R
that very much resembles what you would write in SAS®. These functions
provide a higher-level programming interface than is typically found in
R, and can therefore make your analysis more efficient and
productive.
Included Packages
The sassy meta-package contains the following
packages:
- logr:
Produces a traceable log
- fmtr:
Provides functions for formatting data and a creating a format
catalog
- libr: Gives
you the ability to define a libname, generate a data dictionary, and
simulate a data step
- reporter: A reporting
package with easy layout capabilities and the ability to write reports
in TXT, RTF, PDF, and DOCX file formats
- common: A
set of utility functions shared across the sassy family
of packages, and often useful in their own right.
- procs: A
set of functions that simulate SAS® procedures. Package includes
simulations of PROC FREQ, PROC MEANS, PROC TRANSPOSE, PROC SORT, and
PROC PRINT.
The above links will take you into the respective packages for a deep
dive on their capabilities.
Next Steps
Before taking a deep dive into the sassy package
documentation, please look at some examples. These examples will give
you a feel for the overall flow of a sassy-enhanced
program, and allow you to see how the functions work together.
The following examples are provided on this site:
Example 1:
Creates a simple data listing and log
Example 2: Creates a
table of demographic characteristics
Example 3:
Creates a simple figure
Example 4: Creates
an AE table with a page wrap
Example 5: Creates a
table of vital signs statistics
Example 6:
Creates a figure with a by-group
Example 7:
Perform survival analysis.
Example 8:
Creates a patient profile report.
Example 9:
Creates a figure with a forest plot.
Example 10: Creates
a subject disposition table.
Example 11:
Creates a subject listing with vital signs by visit.
Example 12:
Creates a combined figure of age groups by treatment.
Example 13:
Creates a Mean Change from Baseline figure for laboratory values.
Example 14: Creates
an AE table with severity grades in rows
Example 15:
Creates both stand-alone and “intext” versions of a demographics table.
Example 16:
Creates a shift table of lab values.
Once you review these examples, please proceed to the package links
above to explore the system further!