Description Usage Arguments Value Author(s) See Also

View source: R/updateModel.Bin.R

This function will take the frequency-ranked set of variables and will generate a new model with terms that meet either the integrated discrimination improvement (IDI), or the net reclassification improvement (NRI), threshold criteria.

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`Outcome` |
The name of the column in |

`covariates` |
A string of the type "1 + var1 + var2" that defines which variables will always be included in the models (as covariates) |

`pvalue` |
The maximum |

`VarFrequencyTable` |
An array with the ranked frequencies of the features, (e.g. the |

`variableList` |
A data frame with two columns. The first one must have the names of the candidate variables and the other one the description of such variables |

`data` |
A data frame where all variables are stored in different columns |

`type` |
Fit type: Logistic ("LOGIT"), linear ("LM"), or Cox proportional hazards ("COX") |

`lastTopVariable` |
The maximum number of variables to be tested |

`timeOutcome` |
The name of the column in |

`selectionType` |
The type of index to be evaluated by the |

`maxTrainModelSize` |
Maximum number of terms that can be included in the model |

`zthrs` |
The z-thresholds estimated in forward selection |

`final.model` |
An object of class |

`var.names` |
A vector with the names of the features that were included in the final model |

`formula` |
An object of class |

`z.selectionType` |
A vector in which each term represents the |

Jose G. Tamez-Pena and Antonio Martinez-Torteya

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