- Bug fix for GAM-based losses
- Replaces gbm implementation with xgboost using a custom loss function
- Adds vignette for estimation of flexible ITRs via xgboost
- Various small improvements/bug fixes
- Added changes to reflect the incoming JSS publication related to this package
- The DOI in the CITATION is for a new JSS publication that will be registered after publication on CRAN.
- Adds utilities for construction of augmentation functions and propensity score fitting functions
- Adds vignette for multi-category treatments and for usage of augmentation/propensity score utilities
- Various bug fixes
- Added warning for use of Harrell's procedure in high dimensions
- Changed default value for 'train.fraction' to 0.75 from 0.5 in 'validate.subgroup'
- Minor improvements to plotting for 'subgroup_validated' objects
- Fixes trt factor level reordering issue for plots
- Fixes model printing error
- Improves subgroup.summarize() output
- Fixes default argument bug for r-oldrel + windows
- Simplified plot labeling
- Added clarifications to documentation
- Added customized loss function option
- Added options for count outcomes via Poisson negative log-likelihood as the loss
- Added treatment effect calculation based on estimated benefit scores
- Clarified/improved printing
- Improved numerical stability of weighted.ksvm
- Added printing of subgroup_validated results for quantile cutoffs via the which.quant argument
- Added plots of means within treatment groups as the benefit scores are varied
- Added quantile and median cutpoints as options
- Fixes subgroup effect calculation to account for weights
- Added NSW Study dataset
- Added requirement for latest version of glmnet. old versions throw error when efficiency augmentation used
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Fixed minor bugs regarding multiple treatment options, match.id
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Added OWL-type losses: logistic and hinge surrogates (multiple treatment available for logistic surrogate)
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Added outcome flipping OWL-type losses: logistic and hinge surrogates
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Added augmentation option for non-continuous outcomes via offset
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Added estimation functionality for multiple treatments
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Updated all plot and summary type functions to properly handle results for multiple treatments
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Aaron added plotting option for validation objects that allows the user to inspect the distribution of variable selections over the bootstrap or training/test resampling iterations
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Added more options to printing of validation objects
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Updated check.overlap() to handle multiple treatments
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Aaron added match.id argument to allow proper analysis of matched case-control datasets