gsm.reporting

The {gsm} ecosystem provides a standardized Risk Based Quality Monitoring (RBQM) framework for clinical trials that pairs a flexible data pipeline with robust reports like the one shown below.

The {gsm.reporting} package provides the necessary functions and workflows to produce the reporting data model that is used by many packages to produce visualizations and reports. This README provides a high-level overview of {gsm.reporting}; see the gsm Reporting Vignette for additional details.

With all necessary inputs to the reporting model created via functions in {gsm.mapping} and {gsm.core}, {gsm.reporting} generates the reporting data model data frames. These data frames created are as follows:

1. dfGroups: Group-level metadata dictionary. Created by passing CTMS site and study data to MakeLongMeta().
2. dfMetrics: Metric-specific metadata for use in charts and reporting. Created by passing an lWorkflow object to MakeMetric().
3. dfResults: A stacked summary of analysis pipeline output. Created by passing a list of results returned by Summarize() to BindResults().
4. dfBounds: Set of predicted percentages/rates and upper- and lower-bounds across the full range of sample sizes/total exposure values for reporting. Created by passing dfResults and dfMetrics to MakeBounds().

Installation

You can install the development version of gsm.reporting like so:

# install.packages("pak")
pak::pak("Gilead-BioStats/gsm.reporting@dev")