Stuart G. Baker, 2014
A predictive marker is a baseline variable in a randomized trial that is used to determine subgroups in which the effect of treatment is greater than average. This software uses a modified adaptive signature design to evaluate a randomized trial with a binary outcome and multiple baseline variables (possibly high dimensional). The software splits the data into training and test samples. For the training sample the software fits various benefit functions. A fundamental option is whether to use cross-validation in the training sample to select the best set of benefit functions (Method 1) or directly fit models in training sample (Method 2). For the test sample the software computes benefit scores based on the benefit function and treatment effect in subgroups with benefit scores greater than cutpoints. The software plots estimated treatment effect versus cutpoint, which is similar to a tail-oriented subpopulation treatment effect pattern plot.
Mathematica Version 8 or later.
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Last updated: July 30, 2014
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