Experimental Design and Inference

EDI

Details

Provides comprehensive support for many fixed and sequential experimental designs and many infererential methods (parametric, nonparametric, exact) for response types continuous, incidence, count, proportion, survival (with censoring) and ordinal. Supports automatic missing data imputation, parallelization, provides robustness fallbacks and is optimized with C++.

References

Adam Kapelner and Abba Krieger A Matching Procedure for Sequential Experiments that Iteratively Learns which Covariates Improve Power, Arxiv 2010.05980

See also

Useful links:

• https://github.com/kapelner/EDI

• https://kapelner.github.io/EDI/

• https://pypi.org/project/edi-kernels/

• Report bugs at https://github.com/kapelner/EDI/issues

Author

Adam Kapelner kapelner@qc.cuny.edu