R: Study Strap and Multi-Study Learning Algorithms

# Study Strap and Multi-Study Learning Algorithms

## Documentation for package ‘studyStrap’ version 1.0.0

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

cmss | Covariate-Matched Study Strap for Multi-Study Learning: Fits accept/reject algorithm based on covariate similarity measure
fatTrim | fatTrim: Supporting function to reduce the size of models
merged | Merged Approach for Multi-Study Learning: fits a single model on all studies merged into a single dataframe.
sim.metrics | Study Strap similarity measures: Supporting function used as the default similarity measures in Study Strap, SSE, and CMSS algorithms. Compares similarity in covaraite profiles of 2 studies.
ss | The Study Strap for Multi-Study Learning: Fits Study Strap algorithm
sse | Trained-on-Observed-Studies Ensemble (Study-Specific Ensemble) for Multi-Study Learning: fits one or more models on each study and ensembles models.
studyStrap.predict | Study Strap Prediction Function: Makes predictions on object of class "ss"