CompCausal: Inferring causal effects in comprehensive cohort studies

This package provide R implementations of the estimation methods for inferring causal effects in comprehensive cohort studies, in the presence of unmeasured confounding and missing outcomes. The causal effects include comprehensive cohort causal effects, randomized trial causal effects, and patient preference causal effect.

See also

Useful links:

• https://github.com/UofUEpiBio/CompCausal

• https://uofuepibio.github.io/CompCausal/

• Report bugs at https://github.com/UofUEpiBio/CompCausal/issues

Author

Maintainer: Jennifer Xu jennifer.xu@hsc.utah.edu

Authors:

• Daniel Scharfstein daniel.scharfstein@hsc.utah.edu (ORCID) [project director]

Other contributors:

• George Vega Yon g.vegayon@gmail.com (ORCID) [contributor]