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Rejoinder: Improving precision and power in randomized trials for COVID-19 treatments using covariate adjustment, for binary, ordinal, and time-to-event outcomes.
Benkeser, David; Díaz, Iván; Luedtke, Alex; Segal, Jodi; Scharfstein, Daniel; Rosenblum, Michael.
  • Benkeser D; Department of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia, USA.
  • Díaz I; Division of Biostatistics, Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA.
  • Luedtke A; Department of Statistics, University of Washington, Seattle, Washington, USA.
  • Segal J; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
  • Scharfstein D; Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
  • Rosenblum M; Division of Biostatistics, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, Utah, USA.
Biometrics ; 77(4): 1492-1494, 2021 12.
Article in English | MEDLINE | ID: covidwho-1247135
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Drug Treatment Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: Biometrics Year: 2021 Document Type: Article Affiliation country: Biom.13495

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Drug Treatment Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: Biometrics Year: 2021 Document Type: Article Affiliation country: Biom.13495