Description Usage Arguments Value Author(s) References

View source: R/MEsvm.R View source: R/MEsvm.R

Train a Mixed Effect support vector machine for binary outcome.

1 2 3 4 |

`form` |
formula |

`dat` |
data.frame with predictors |

`groups` |
character name of the column containing the group identifier |

`rand.vars` |
random effect variables |

`para` |
named list of gbm training parameters |

`tol` |
convergence tolerance |

`max.iter` |
maximum number of iterations |

`include.RE` |
(logical) to include random effect Zb as predictor in gbm? |

`verbose` |
verbose for lme4 |

`likelihoodCheck` |
(logical) to use log likelihood of glmer to check for convergence? |

`...` |
Further arguments passed to or from other methods. |

`lme.family` |
glmer control |

`type` |
of predictions of gbm to pass to lme4 as population estimates (these will be used as offset) |

An object of class MEgbm; a list with items

`svmfit` |
fitted svm model |

`glmer.fit` |
fitted mixed effect logistic regression model |

`logLik` |
log likelihood of mixed effect logistic regression |

`random.effects` |
random effect parameter estimates |

`svm.form` |
svm formula for fitted model |

`glmer.form` |
lmer4 formula |

`glmer.CI` |
estimates of mixed effect logistic regression with approximate confidence intervals on the logit scale. More accurate values can be obtained by bootstrap |

`fitted.probs` |
fitted probabilites for final model |

`fitted.class` |
fitted class labels for final model |

`fitted.decision` |
fitted decision values for final model |

`train.perf` |
various performance measures for final model on training set |

`threshold` |
classification cut-off |

Che Ngufor <[email protected]>

Che Ngufor, Holly Van Houten, Brian S. Caffo , Nilay D. Shah, Rozalina G. McCoy Mixed Effect Machine Learning: a framework for predicting longitudinal change in hemoglobin A1c, in Journal of Biomedical Informatics, 2018

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.