Optimising precision and power by machine learning in randomised trials with ordinal and time-to-event outcomes with an application to COVID-19

Williams, N., Rosenblum, M., & Díaz, I. (2022). Optimising Precision and Power by Machine Learning in Randomised Trials with Ordinal and Time-to-Event Outcomes with an Application to COVID-19. Journal of the Royal Statistical Society Series A: Statistics in Society, 185(4), 2156–2178. https://doi.org/10.1111/rssa.12915
Authors:
Nicholas Williams
Michael Rosenblum
Iván Díaz
Affiliated Authors:
Nicholas Williams
Columbia Affiliation:
Author Keywords:
asymptotic normality
covariate adjustment
efficiency gains
machine learning
marginal treatment effect
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Publication Type:
Article
Unique ID:
10.1111/rssa.12915
DOI:
10.1111/rssa.12915
Journal:
Journal of the Royal Statistical Society, Series A: Statistics in Society
Publication Date:
Data Source:
Scopus
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