![[R logo]](../../../doc/html/logo.jpg){kind=logo}
![[Up]](../../../doc/html/left.jpg)
![[Top]](../../../doc/html/up.jpg)
| SubgrpID-package | Patient subgroup identification for clinical drug development |
| aim.batting | The main AIM-BATTing function |
| aim.batting.wrapper | Wrapper function for cv.aim.batting to be passed to kfold.cv. |
| aim.rule.batting | The main AIM-Rule-BATTing function |
| aim.rule.batting.wrapper | Wrapper function for aim.rule.batting, to be passed to kfold.cv |
| aim.score.pred | Find score of cutoff (returned by aim.find.cutoff.pred) for predictive case. |
| aim.score.prog | Find score of cutoff (returned by aim.find.cutoff.pred) for prognostic case. |
| backfit.cox.interaction | An internal function used in cox.interaction |
| balanced.folds | Create balanced folds for cross-validation. |
| batting.pred | Main predictive BATTing function |
| batting.prog | Main prognostic BATTing function |
| binary.stats | A function for binary statistics |
| combine.condition | Internal function |
| cox.interaction | Interaction Cox AIM |
| create.training.dataset.index | create training/testing dataset indexes. |
| cv.aim.batting | The function for CV in aim.batting |
| cv.aim.rule.batting | The function for CV in aim.rule.batting |
| cv.cox.interaction | A function for CV in Cox AIM with interaction. |
| cv.cox.main | A function for the number of binary rules in the main effect AIM with time to event outcome |
| cv.folds | Cross-validation folds. |
| cv.lm.interaction | A function for CV in linear AIM with interaction. |
| cv.lm.main | A function for the number of binary rules in the main effect AIM with continuous outcome |
| cv.logistic.interaction | A function for CV in logistic AIM with interaction. |
| cv.logistic.main | A function for the number of binary rules in the main effect AIM with binary outcome |
| cv.pval | p-value calculation for each iteration of cross validation. |
| cv.seqlr.batting | Cross Validation for Sequential BATTing |
| evaluate.cv.results | Cross-validation Performance Evaluation |
| evaluate.results | Get statistics for a single set of predictions. |
| filter | Filter function for predictive/prognostic biomarker candidates for signature development |
| filter.glmnet | Flitering using MC glmnet |
| filter.unicart | rpart filtering (only for prognostic case) |
| filter.univariate | Univariate Filtering |
| find.pred.stats | Find predictive stats from response and prediction vector |
| find.prog.stats | Find prognostic stats from response and prediction vector |
| get.var.counts.aim | Get counts of signature variables from output of cv.aim.batting. |
| get.var.counts.seq | Get signature variables from output of seqlr.batting. |
| interaction.plot | A function for interaction plot |
| kfold.cv | Perform k-fold cross-validation of a model. |
| make.arg.list | Create a list of variables corresponding to the arguments of the function func.name and assigns values. |
| one.dropping | Perform dropping one time in predictive case. |
| one.dropping.prog | Perform dropping one time in prognostic case. |
| one.pasting | Perform pasting one time in predictive case. |
| one.pasting.prog | Perform pasting one time in prognostic case. |
| one.peeling | Perform peeling one time in predictive case. |
| one.peeling.prog | Perform peeling one time in prognostic case. |
| permute.rows | Ramdomly permute the rows of a matrix. |
| permute.vector | Randomly permute the entries of a vector. |
| pred.aim | Make predictions for data given prediction rule in predict.rule. |
| pred.aim.cv | Make predictions for data given prediction rule in predict.rule |
| pred.prim | Prediction function for PRIM |
| pred.prim.cv | Prediction function for PRIM CV |
| pred.seqlr | Prediction function for Sequential BATTing |
| pred.seqlr.cv | Prediction function for CV Sequential BATTing |
| prim.cv | Cross-validation for PRIM |
| prim.train | The main PRIM function |
| prim.train.pred.once | Apply PRIM one time on the training data for a fixed value of alpha in predictive case |
| prim.train.prog.once | Apply PRIM one time on the training data for a fixed value of alpha (in prognostic case) |
| prim.train.wrapper | Wrapper function for PRIM CV |
| pval.cal | Calculate p-value for treatment in each subgroup in predictive case |
| pval.cal.prog | Calculate p-value for treatment in each subgroup in prognostic case |
| query.data | internal function used in seqlr.batting |
| query.from.condition | An internal function inside one.pasting. |
| resample | Creates a permutation of given size. |
| Sepsis.test | Sepsis Trial testing dataset |
| Sepsis.train | Sepsis Trial training dataset |
| seqlr.batting | Perform sequential BATTing method. |
| seqlr.batting.wrapper | Wrapper function for seqlr.batting, to be passed to kfold.cv. |
| seqlr.find.cutoff.pred | Find cutoff for predictive case. |
| seqlr.find.cutoff.prog | Find cutoff for prognostic case. |
| seqlr.score.pred | Compute score of cutoff for predictive case |
| seqlr.score.prog | Compute score of cutoff for prognostic case |
| SubgrpID | Exploratory Subgroup Identification main function |
| summarize.cv.stats | Calculate summary statistics from raw statistics returned by evaluate.cv.results. |