Variance estimators for weighted and stratified linear dose–response function estimators using generalized propensity score-Reference-Cited by-同舟云学术

Variance estimators for weighted and stratified linear dose–response function estimators using generalized propensity score

Published:2021-07-29 Issue:1 Volume:64 Page:33-56
ISSN:0323-3847
Container-title:Biometrical Journal
language:en
Short-container-title:Biometrical J

Author:

Garès Valérie¹,Chauvet Guillaume²,Hajage David³^ORCID

Affiliation:

1. Univ Rennes INSA, CNRS, IRMAR ‐ UMR 6625, F‐35000 Rennes France

2. Univ Rennes ENSAI, CNRS, IRMAR ‐ UMR 6625, F‐35000 Rennes France

3. Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique, AP‐HP, Hôpital Pitié‐Salpêtrière, Département de Santé Publique Centre de Pharmacoépidémiologie Paris France

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,General Medicine,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/bimj.202000267

Reference46 articles.

1. Matching on the Estimated Propensity Score

2. Angelo C. &Ripley B.D.(2020).boot: Bootstrap R. (S‐Plus) Functions2020. R. package version 3–25.

3. Some Methods of Propensity-Score Matching had Superior Performance to Others: Results of an Empirical Investigation and Monte Carlo simulations

4. The performance of different propensity score methods for estimating marginal hazard ratios

5. Variance estimation when using inverse probability of treatment weighting (IPTW) with survival analysis

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