A prediction-based approach to the analysis of data from randomized clinical trials is implemented. Based on response and covariate data from a randomized clinical trial comparing a new experimental treatment E versus a control C, the objective is to develop and internally validate a model that can identify subjects likely to benefit from E rather than C. Currently, survival and binary response types are permitted.
|Author||Jyothi Subramanian [aut, cre], Richard Simon [aut]|
|Date of publication||2016-04-15 23:39:12|
|Maintainer||Jyothi Subramanian <email@example.com>|
EORTC10994: EORTC10994 dataset
eval.pact.cv: Evaluation functions for cross-validated predictions
GSE10846: GSE10846 dataset
KfoldCV: Split a dataset into k parts for k-fold cross-validation
overall.analysis: Overall statistics and inference
pact: Predictive Analysis of Clinical Trials
pact.cv: Cross-validation for pact
pact.fit: Fits a predictive model to the full dataset
predict.pact: Predictions from a predictive model fit
print.eval.cv: Print an object of class 'eval.cv'
print.pact: Print an object of class 'pact'
prostateCancer: Prostate cancer dataset
summary.pact: Summarize a predictive model fit
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