Propensity Score Methods for Confounding Control in Observational Studies of Therapeutics for COVID-19 Infection

The authors provide a brief overview of different propensity score methods that can be used in observational research studies that lack randomization. Under specific assumptions, these methods result in unbiased estimates of causal effects, but the different ways propensity scores are used may require different assumptions and result in estimated treatment effects that can have meaningfully different interpretations. The authors review these issues and consider their implications for studies of therapeutics for coronavirus disease 2019.

Authors

Institutions

Publication Details

Journal
Clinical Infectious Diseases
Published
2024-10-16
DOI
https://doi.org/10.1093/cid/ciae516
Citations
4
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
2.84
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Propensity Score Methods for Confounding Control in Observational Studies of Therapeutics for COVID-19 Infection

M. Alan Brookhart, Nuvan Rathnayaka, Kayla Hendrickson, Kathleen E. Hurwitz
4 citations
Clinical Infectious Diseases
Advanced Causal Inference Techniques
2.84
article

Propensity Score Methods for Confounding Control in Observational Studies of Therapeutics for COVID-19 Infection

M. Alan Brookhart, Nuvan Rathnayaka, Kayla Hendrickson, Kathleen E. Hurwitz
article en
4 citations

Abstract

The authors provide a brief overview of different propensity score methods that can be used in observational research studies that lack randomization. Under specific assumptions, these methods result in unbiased estimates of causal effects, but the different ways propensity scores are used may require different assumptions and result in estimated treatment effects that can have meaningfully different interpretations. The authors review these issues and consider their implications for studies of therapeutics for coronavirus disease 2019.

Clinical Infectious DiseasesVol. 79(Supplement_4)
Target (United States) (US), Duke University (US)
Good health and well-being
Openalex Percentile: Top 9%
Advanced Causal Inference Techniques
2.84
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.