NEWS

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TreatmentSelection 2.1.1 (2017-08-11)

• Update trtsel man files specifying that larger values of a continuous outcome should be associated with worse outcomes.

TreatmentSelection 2.1.0 (2017-07-25)

Two key additions:

• allow continuous and time-to-event outcomes
• allow a user to evaluate models with more than one marker

One minor additions:

• updated the estimator of event rate under marker based treatment.

TreatmentSelection 2.0.4

• adjusted estimate of event rate under marker-based trt.

TreatmentSelection 2.0.3 (2017-02-09)

Note: This is a large update with many changes. Although, the estimation methods remain the same, many of the functions inputs have changed. This is to accomodate multivariate models and survival outcomes.

• Addition of 'trtsel_measures': a simple function for evaluating the performance of a user-specified marker-based treatment rule.
• Input formulas into trtsel objects instead of univariate marker information. This allows for the evaluation of multivariate models.
• The package now allows for survival outcomes.
• Bias-correction to adjust for over-optimism that comes from evaluating models on the same data that were used to fit model parameters. 'eval.trtsel' and 'compare.trtsel' now implements a bootstrap bias-correction method.

TreatmentSelection 1.1.3

• tweaked estimation of Var(Delta) for subcohort designs.

TreatmentSelection 1.1.2 (2014-06-17)

• added plot.type 'selection impact'. see ?plot.trtsel for more information.
• fixed a small bug that caused warnings when plotting a trtsel object created from providing fixed risk estimates.

TreatmentSelection 1.1.1 (2014-04-07)

• eval.trtsel: modeled estimates of event rates calculated for subcohort designs had a bug. Calculations now are correct.
• eval.trtsel: also fixed bug where event rates werent calculated when bootstraps = 0.
• eval.trtsel: fixed event rate labeling bug that swapped trt all for trt none.
• plot.trtsel: added new plot.type that plots event rate under different marker based treatment assignment rules vs. F_delta(v).
• plot.trtsel: the mean trt effect line for subcohort designs was not weighted correctly. this has been fixed for continuous and discrete markers.
• plot.trtsel: fixed a bug building plots for subcohort designs with discrete markers
• fixed various small things so that the package now has no warnings from R CMD Check
• added manual files for tsdata_scc and tsdata_cc
• calibrate.trtsel: fixed bug when calibrating models fit using stratified case-control data.