Response to Harrell’s commentary-Reference-Cited by-同舟云学术

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Response to Harrell’s commentary

Published:2024-06-02 Issue:4 Volume:21 Page:415-417
ISSN:1740-7745
Container-title:Clinical Trials
language:en
Short-container-title:Clinical Trials

Author:

Van Lancker Kelly¹^ORCID,Bretz Frank²³^ORCID,Dukes Oliver¹

Affiliation:

1. Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium

2. Novartis Pharma AG, Basel, Switzerland

3. Section of Medical Statistics, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria

Funder

Bijzonder Onderzoeksfonds UGent

Fonds Wetenschappelijk Onderzoek

Publisher

SAGE Publications

Link

https://journals.sagepub.com/doi/pdf/10.1177/17407745241251851

Reference23 articles.

1. Improving precision and power in randomized trials for COVID‐19 treatments using covariate adjustment, for binary, ordinal, and time‐to‐event outcomes

2. Huitfeldt A, Fox MP, Murray EJ, et al. Shall we count the living or the dead?2021, https://arxiv.org/pdf/2106.06316

3. Conditioning on the propensity score can result in biased estimation of common measures of treatment effect: A Monte Carlo study (p n/a) by Peter C. Austin, Paul Grootendorst, Sharon-Lise T. Normand, Geoffrey M. Anderson,Statistics in Medicine, Published Online: 16 June 2006. DOI: 10.1002/sim.2618

4. Randomization Does Not Justify Logistic Regression

5. Simple, Efficient Estimators of Treatment Effects in Randomized Trials Using Generalized Linear Models to Leverage Baseline Variables

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