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goshawk.Rmd
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goshawk.Rmd
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---
title: "Introduction to goshawk"
date: "2022-03-09"
output:
rmarkdown::html_document:
theme: "spacelab"
highlight: "kate"
toc: true
toc_float: true
vignette: >
%\VignetteIndexEntry{Introduction to goshawk}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
editor_options:
markdown:
wrap: 72
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
```
## 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](https://insightsengineering.github.io/goshawk/latest-tag/reference/index.html).
The `goshawk` functions used for plot generation are `g_` prefixed.
All `goshawk` plot functions are listed on [the goshawk website functions reference](https://insightsengineering.github.io/goshawk/latest-tag/reference/index.html) 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](https://insightsengineering.github.io/teal/) is a shiny-based interactive exploration framework for analyzing data.
`teal` shiny apps with `goshawk` outputs are available in the [`teal.goshawk` package](https://insightsengineering.github.io/teal.goshawk/).
## 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](https://insightsengineering.github.io/teal.goshawk/).**
## 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](https://insightsengineering.github.io/goshawk/).**