How to perform prespecified subgroup analyses when using propensity score methods in the case of imbalanced subgroups

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: 1 Online-Ressource.

Language: Englisch

Bibliographic citation: How to perform prespecified subgroup analyses when using propensity score methods in the case of imbalanced subgroups ; volume:23 ; number:1 ; day:31 ; month:10 ; year:2023 ; pages:1-16 ; date:12.2023
BMC medical research methodology ; 23, Heft 1 (31.10.2023), 1-16, 12.2023

Creator: Chatelet, Florian
Verillaud, Benjamin
Chevret, Sylvie

Contributor: SpringerLink (Online service)

DOI: 10.1186/s12874-023-02071-8

URN: urn:nbn:de:101:1-2024011721001617973325

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 2025-08-15T07:24:44+0200

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Chatelet, Florian
Verillaud, Benjamin
Chevret, Sylvie
SpringerLink (Online service)

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Density-based weighting for imbalanced regression

Optimizing neural networks for imbalanced data

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Well-Lotion (Dauerwellflüssigkeit für langes Haar)

WELLA PERFORM

Innovational approach to simultaneously analyze numerous subgroups and to identify subgroup effects in clinical and epidemiological studies

Konferenzschrift

Act, move, perform

Applikator (Pumpe für perform-Dauerwellen)

WELLA PERFORM APPLIKATOR

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Density-based weighting for imbalanced regression

Optimizing neural networks for imbalanced data

Imbalanced regression using regressor-classifier ensembles

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How to perform prespecified subgroup analyses when using propensity score methods in the case of imbalanced subgroups

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Other Objects (12)

Identifying Safety Subgroups at Risk: Assessing the Agreement Between Statistical Alerting and Patient Subgroup Risk

WELLA PERFORM

Innovational approach to simultaneously analyze numerous subgroups and to identify subgroup effects in clinical and epidemiological studies

Act, move, perform

WELLA PERFORM APPLIKATOR

Subgroup growth

Robust subgroup discovery : Discovering subgroup lists using MDL

Bookends perform SIMON & GARFUNKEL

Combining propensity score methods with variational autoencoders for generating synthetic data in presence of latent sub-groups

Density-based weighting for imbalanced regression

Optimizing neural networks for imbalanced data

Imbalanced regression using regressor-classifier ensembles

Identifying Safety Subgroups at Risk: Assessing the Agreement Between Statistical Alerting and Patient Subgroup Risk

WELLA PERFORM

Innovational approach to simultaneously analyze numerous subgroups and to identify subgroup effects in clinical and epidemiological studies

Act, move, perform

WELLA PERFORM APPLIKATOR

Subgroup growth

Robust subgroup discovery : Discovering subgroup lists using MDL

Bookends perform SIMON & GARFUNKEL

Combining propensity score methods with variational autoencoders for generating synthetic data in presence of latent sub-groups

Density-based weighting for imbalanced regression

Optimizing neural networks for imbalanced data

Imbalanced regression using regressor-classifier ensembles

Identifying Safety Subgroups at Risk: Assessing the Agreement Between Statistical Alerting and Patient Subgroup Risk

WELLA PERFORM

Innovational approach to simultaneously analyze numerous subgroups and to identify subgroup effects in clinical and epidemiological studies

Act, move, perform

WELLA PERFORM APPLIKATOR

Subgroup growth

Robust subgroup discovery : Discovering subgroup lists using MDL

Bookends perform SIMON & GARFUNKEL

Combining propensity score methods with variational autoencoders for generating synthetic data in presence of latent sub-groups

Density-based weighting for imbalanced regression

Optimizing neural networks for imbalanced data

Imbalanced regression using regressor-classifier ensembles

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