Introduction
This vignette shows the general purpose and syntax of the
goshawk R package. The goshawk R package
contains analytical functions for primarily creating longitudinal
visualizations useful for clinical trials and other statistical
analysis.
Common Clinical Trials Analyses
The package provides several functions to create graphs used for clinical trials and other statistical analyses.
data visualizations:
- box plots
- correlation and scatter plots
- density distribution plots
- line plots
- spaghetti plots
data tables:
- box, density and line plots are accompanied by tables displaying descriptive statistics
data brushing:
- box, correlation and spaghetti plots include data brushing functionality used to display details of data points displayed in the plots
The reference of goshawk functions is available on the
goshawk website functions reference.
The goshawk functions used for plot generation are
g_ prefixed. All goshawk plot functions are
listed on the
goshawk website functions reference and include examples of data
pre-processing and function usage. Please see the Articles for more
information on data pre-processing and data expectations for
goshawk.
Interactive Apps
The goshawk outputs can be easily accommodated into
shiny apps. We recommend applying goshawk
outputs into teal apps. The teal
package is a shiny-based interactive exploration framework for
analyzing data. teal shiny apps with goshawk
outputs are available in the teal.goshawk
package.
Data Requirements
goshawk and teal.goshawk have similar data
related requirements so we chose to document those in the
teal.goshawk package.
For more detail on these requirements please visit the teal.goshawk website.
Summary
In summary, goshawk contains functions for creating
primarily longitudinal visualizations used in clinical trials and other
statistical analyses. The design of the package gives users a lot of
flexibility to meet the analysis needs in a regulatory or exploratory
reporting context.
For more information please explore the goshawk website.