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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.
The sassy meta-package contains the following packages:
The above links will take you into the respective packages for a deep dive on their capabilities.
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!
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