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nbpMatching - Functions for Optimal Non-Bipartite Matching

Perform non-bipartite matching and matched randomization. A "bipartite" matching utilizes two separate groups, e.g. smokers being matched to nonsmokers or cases being matched to controls. A "non-bipartite" matching creates mates from one big group, e.g. 100 hospitals being randomized for a two-arm cluster randomized trial or 5000 children who have been exposed to various levels of secondhand smoke and are being paired to form a greater exposure vs. lesser exposure comparison. At the core of a non-bipartite matching is a N x N distance matrix for N potential mates. The distance between two units expresses a measure of similarity or quality as mates (the lower the better). The 'gendistance()' and 'distancematrix()' functions assist in creating this. The 'nonbimatch()' function creates the matching that minimizes the total sum of distances between mates; hence, it is referred to as an "optimal" matching. The 'assign.grp()' function aids in performing a matched randomization. Note bipartite matching can be performed using the prevent option in 'gendistance()'.

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6.51 score 9 stars 7 dependents 86 scripts 436 downloads

pkdata - Creates Pharmacokinetic/Pharmacodynamic (PK/PD) Data

Prepare pharmacokinetic/pharmacodynamic (PK/PD) data for PK/PD analyses. This package provides functions to standardize infusion and bolus dose raw data obtained from electronic health record (EHR) databases while linking it to drug level or concentration data.

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3.48 score 2 stars 1 dependents 8 scripts 203 downloads

packageDiff - Compare R Package Differences

It provides utility functions for investigating changes within R packages. The pkgInfo() function extracts package information such as exported and non-exported functions as well as their arguments. The pkgDiff() function compares this information for two versions of a package and creates a diff file viewable in a browser.

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3.30 score 4 stars 1 scripts 197 downloads