Multivariate and Propensity Score Matching Software with Automated Balance Optimization: TheMatchingPackage forR | Zendy

Jasjeet S. Sekhon | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Multivariate and Propensity Score Matching Software with Automated Balance Optimization: TheMatchingPackage forR

Author(s) -

Jasjeet S. Sekhon

Publication year - 2011

Publication title -

journal of statistical software

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 7.636

H-Index - 145

ISSN - 1548-7660

DOI - 10.18637/jss.v042.i07

Subject(s) - univariate , multivariate statistics , matching (statistics) , covariate , propensity score matching , computer science , balance (ability) , genetic algorithm , r package , optimal matching , multivariate analysis , data mining , statistics , mathematics , machine learning , programming language , biology , neuroscience

Matching is an R package which provides functions for multivariate and propensity score matching and for finding optimal covariate balance based on a genetic search algorithm. A variety of univariate and multivariate metrics to determine if balance actually has been obtained are provided. The underlying matching algorithm is written in C++, makes extensive use of system BLAS and scales efficiently with dataset size. The genetic algorithm which finds optimal balance is parallelized and can make use of multiple CPUs or a cluster of computers. A large number of options are provided which control exactly how the matching is conducted and how balance is evaluated.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research