select_minimal_grouping_cols

This function identifies the smallest set of columns in a data frame whose unique combinations
can reconstruct the grouping structure defined by the specified strata columns.
It removes duplicate, constant, and redundant columns, then searches for the minimal combination
that uniquely identifies each stratum.

An interactive 'shiny' application for performing non-compartmental analysis (NCA) on
pre-clinical and clinical pharmacokinetic data. The package builds on 'PKNCA' for core estimators and provides interactive visualizations, CDISC
outputs ('ADNCA', 'PP', 'ADPP') and configurable TLGs (tables, listings, and graphs). Typical use cases include exploratory
analysis, validation, reporting or teaching/demonstration of NCA methods. Methods and core
estimators are described in Denney, Duvvuri, and Buckeridge (2015) "Simple, Automatic
Noncompartmental Analysis: The PKNCA R Package" <doi:10.1007/s10928-015-9432-2>.

Valentin Legras

aNCA

(Pre-)Clinical NCA in a Dynamic Shiny App

Ercan Suekuer

Gerardo Jose Rodriguez

Pascal Baertschi

Jana Spinner

Mateusz Kolomanski

Lucy Aspridis

F. Hoffmann-La Roche AG 

select_minimal_grouping_cols function

<dl><dt>df</dt>
<dd>A data frame.</dd>
<dt>strata_cols</dt>
<dd>Column names in df whose unique combination defines the strata.</dd></dl>

Arguments

Find Minimal Grouping Columns for Strata Reconstruction — select_minimal_grouping_cols

<dl>

<dt>df</dt>
<dd>A data frame.</dd>


<dt>strata_cols</dt>
<dd>Column names in df whose unique combination defines the strata.</dd>

</dl>

select_minimal_grouping_cols: Find Minimal Grouping Columns for Strata Reconstruction

Description

Usage

Value

Arguments