Two (almost) are ready. causatr is the engine: g-formula and ICE g-computation, IPW, doubly-robust AIPW, structural nested mean models, matching (with sandwich and bootstrap variance).
etverse.github.io/causatr/
Still cooking: matchatr (case-control / nested CC / case-cohort) and negatr (negative-control methods). DAGs, target-trial emulation and bias analysis after that.
Early days, would love your feedback.
github.com/etverse
survatr is the survival side: pooled-logistic hazard g-computation, IPW and ICE for time-to-event outcomes, risk-difference and RMST contrasts, competing risks. Runs on person-period data.
etverse.github.io/survatr/
I am extremely happy to have been awarded, apparently, a Juan de la Cierva postdoctoral fellowship from @ageinves.bsky.social to “continue” (I just started) my work at @cniostopcancer.bsky.social with Nuria Malats. 🥹
#cancer #episky
I am extremely happy to have been awarded, apparently, a Juan de la Cierva postdoctoral fellowship from @ageinves.bsky.social to “continue” (I just started) my work at @cniostopcancer.bsky.social with Nuria Malats. 🥹
#cancer #episky