Improved precision in the analysis of randomized trials with survival outcomes, without assuming proportional hazards

@BertrandBio Here is an example https://t.co/mVCnn87gjT

RT @ildiazm: @ProfMattFox @ADAlthousePhD Forget about imbalance, never check it, always adjust for everything that's predictive of the outc…

RT @ildiazm: @ProfMattFox @ADAlthousePhD Forget about imbalance, never check it, always adjust for everything that's predictive of the outc…

RT @ildiazm: Some examples of paper that do the above: 22/ https://t.co/gswfsabTpb https://t.co/phPx71u7Lc https://t.co/qDcexrPpk3 https://…

Some examples of paper that do the above: 22/ https://t.co/gswfsabTpb https://t.co/phPx71u7Lc https://t.co/qDcexrPpk3 https://t.co/0uGb4Ia1OA https://t.co/LDbs6mTuqG

@VictorDayan1 @f2harrell @kaulcsmc They did not use a covariate adjustment technique that is robust to model misspecification. Below is one approach that could be adapted to estimate cumulative incidence functions. IMO, Fine&Gray/proportional hazards i

RT @ildiazm: @ProfMattFox @ADAlthousePhD Forget about imbalance, never check it, always adjust for everything that's predictive of the outc…

@ProfMattFox @ADAlthousePhD Forget about imbalance, never check it, always adjust for everything that's predictive of the outcome. Worst case scenario your estimator is like the unadjusted, best case scenario you gain efficiency: https://t.co/qDcexrPpk3

Improved precision in the analysis of randomized trials with survival outcomes, without assuming proportional hazards. Iván Díaz, Elizabeth Colantuoni, Daniel F. Hanley, Michael Rosenblum. Lifetime Data Analysis. https://t.co/1BycxQMyXW

RT @ildiazm: Because covariate adjustment can increase efficiency (e.g., https://t.co/JryPR1uGgG, https://t.co/hdQoY8a2Hs, https://t.co/4jQ…

@ignaziano @BenListyg @alexpghayes @economeager @EpiEllie @deaneckles Check these papers out. Maybe they are what you are looking for. https://t.co/xZSY3cV6md https://t.co/4qVQ8SoiaP https://t.co/Om0BVSZzu6 https://t.co/pW4dGQ2Uzq

RT @ildiazm: Because covariate adjustment can increase efficiency (e.g., https://t.co/JryPR1uGgG, https://t.co/hdQoY8a2Hs, https://t.co/4jQ…

RT @ildiazm: Because covariate adjustment can increase efficiency (e.g., https://t.co/JryPR1uGgG, https://t.co/hdQoY8a2Hs, https://t.co/4jQ…

Because covariate adjustment can increase efficiency (e.g., https://t.co/JryPR1uGgG, https://t.co/hdQoY8a2Hs, https://t.co/4jQIGZ2sBl). Because loss to follow up effectively makes your trial an observational study. Because you want to estimate optimal trea