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Cited by 253

The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.

Propensity Score Matching with Time‐Dependent Covariates

Lu, Bo·2005·Biometrics

Abstract

SummaryIn observational studies with a time‐dependent treatment and time‐dependent covariates, it is desirable to balance the distribution of the covariates at every time point. A time‐dependent propensity score based on the Cox proportional hazards model is proposed and used in risk set matching. Matching on this propensity score is shown to achieve a balanced distribution of the covariates in both treated and control groups. Optimal matching with various designs is conducted and compared in a study of a surgical treatment, cystoscopy and hydrodistention, given in response to a chronic bladder disease, interstitial cystitis. Simulation studies also suggest that the statistical analysis after matching outperforms the analysis without matching in terms of both point and interval estimations.

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Crossref · 10.1111/j.1541-0420.2005.00356.x

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Metadata

Authors
Lu, B.
Venue
Biometrics
Published
2005-08-31
Volume
61
Issue
3
Pages
721-728
ISSN
  • 0006-341X (ISSN-L)
  • 1541-0420
OpenAlex
W1963628844
Cited by
253
References
25
FWCI
1.87
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Propensity Score Matching with Time‐Dependent Covariates. https://app.cochat.ai/papers/10.1111/j.1541-0420.2005.00356.x
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Lu, B. (2005). Propensity Score Matching with Time‐Dependent Covariates. Biometrics. https://doi.org/10.1111/j.1541-0420.2005.00356.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.