67 citations · 79 across the 10 of their papers we have counts for
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Learn-As-you-GO (LAGO) Trials: Optimizing Treatments and Preventing Trial Failure Through Ongoing Learning
Ante Bing, Donna Spiegelman, Daniel Nevo +1
It is well known that changing the intervention package while a trial is ongoing does not lead to valid inference using standard statistical methods. However, it is often necessary…
Causal inference with misspecified network interference structure
Bar Weinstein, Daniel Nevo
Under interference, the treatment of one unit may affect the outcomes of other units. Such interference patterns between units are typically represented by a network. Correctly spe…
The Subtype-Free Average Causal Effect for Heterogeneous Disease Etiology
Amit Sasson, Molin Wang, Shuji Ogino +1
Studies have shown that the effect an exposure may have on a disease can vary for different subtypes of the same disease. However, existing approaches to estimate and compare these…
A sensitivity analysis approach for the causal hazard ratio in randomized and observational studies
Rachel Axelrod, Daniel Nevo
The Hazard Ratio (HR) is often reported as the main causal effect when studying survival data. Despite its popularity, the HR suffers from an unclear causal interpretation. As alre…
Matching methods for truncation by death problems
Tamir Zehavi, Daniel Nevo
Even in a carefully designed randomized trial, outcomes for some study participants can be missing, or more precisely, ill-defined, because participants had died prior to date of o…
Causal inference for semi-competing risks data
Daniel Nevo, Malka Gorfine
An emerging challenge for time-to-event data is studying semi-competing risks, namely when two event times are of interest: a non-terminal event time (e.g. age at disease diagnosis…