Abstract
Propensity score matching (PSM) is a technique used in retrospective investigation of cohort matching as an alternative approach to the prospective matching that is typically used by a randomized control trial (RCT). The process of selecting untreated cases that are the best match to the treated cases is the focus of this research. We created a PSM package for the python environment, termed PsmPy, to carry out this task. The PsmPy package debuted and proposed here is based on a logistic regression logit score where a match is selected using k-nearest neighbors (k-NN). Additional plotting and arguments are available to the user and are also described. To benchmark our method, we compared it with the existing R package, MatchIt, and evaluated our covariates' residual effect sizes with respect to the treatment condition before and after matching. Using a Mann-Whitney statistical test, we showed that our method significantly outperformed MatchIt in cohort matching (U=49, p<0.0001) when comparing residual effect sizes of the covariates. The PsmPy demonstrated a 10-fold average improvement in residual effect sizes amongst covariates when compared with the package MatchIt, suggesting that it is a viable alternative for use in propensity matching studies.
Original language | English (US) |
---|---|
Title of host publication | 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1354-1357 |
Number of pages | 4 |
ISBN (Electronic) | 9781728127828 |
DOIs | |
State | Published - 2022 |
Event | 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022 - Glasgow, United Kingdom Duration: Jul 11 2022 → Jul 15 2022 |
Publication series
Name | Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS |
---|---|
Volume | 2022-July |
ISSN (Print) | 1557-170X |
Conference
Conference | 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022 |
---|---|
Country/Territory | United Kingdom |
City | Glasgow |
Period | 7/11/22 → 7/15/22 |
Funding
ACKNOWLEDGMENT The study is supported in part by NIH Grants U01TR003528 and R01LM013337.
Keywords
- COVID-19
- MatchIt
- PsmPy
- Python
- balance
- causal inference
- propensity score matching
ASJC Scopus subject areas
- Signal Processing
- Health Informatics
- Computer Vision and Pattern Recognition
- Biomedical Engineering