Propensity Score Matching: should we use it in designing observational studies?

We conclude that the PSM paradox is not a legitimate concern and should not stop researchers from using PSM designs.

Authors

Institutions

Publication Details

Journal
BMC Medical Research Methodology
Published
2025-01-29
DOI
https://doi.org/10.1186/s12874-025-02481-w
Citations
34
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
89.42
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Propensity Score Matching: should we use it in designing observational studies?

Fei Wan
34 citations
BMC Medical Research Methodology
Advanced Causal Inference Techniques
89.42
article

Propensity Score Matching: should we use it in designing observational studies?

Fei Wan
article en
34 citations

Abstract

We conclude that the PSM paradox is not a legitimate concern and should not stop researchers from using PSM designs.

BMC Medical Research MethodologyVol. 25(1)
Washington University in St. Louis (US)
Openalex Percentile: Top 0%
Advanced Causal Inference Techniques
89.42
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Propensity Score Matching: should we use it in designing observational studies? — Fei Wan · BMC Medical Research Methodology (2025) | TGRS Research Map | TGRS