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")