personalized 0.2.5 2019-11-07

  • 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

personalized 0.2.4 2019-05-22

  • 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

personalized 0.2.3 2019-02-07

  • Fixes trt factor level reordering issue for plots

personalized 0.2.2 2018-11-14

  • Fixes model printing error
  • Improves subgroup.summarize() output

personalized 0.2.1 2018-09-19

  • Fixes default argument bug for r-oldrel + windows

personalized 0.2.0 2018-09-18

  • 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

personalized 0.1.5 2018-04-11

  • Added printing of subgroup_validated results for quantile cutoffs via the which.quant argument

personalized 0.1.4 2018-03-08

  • 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

personalized 0.1.3 2018-01-30

  • Added NSW Study dataset

personalized 0.1.2 2017-11-28

  • Added requirement for latest version of glmnet. old versions throw error when efficiency augmentation used

personalized 0.1.1 2017-10-25

  • Fixed minor bugs regarding multiple treatment options,

  • Added OWL-type losses: logistic and hinge surrogates (multiple treatment available for logistic surrogate)

  • Added outcome flipping OWL-type losses: logistic and hinge surrogates

  • Added augmentation option for non-continuous outcomes via offset

personalized 0.1.0 2017-09-26

  • Added estimation functionality for multiple treatments

  • Updated all plot and summary type functions to properly handle results for multiple treatments

  • 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

  • Added more options to printing of validation objects

  • Updated check.overlap() to handle multiple treatments

  • Aaron added argument to allow proper analysis of matched case-control datasets