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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!
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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