AUCJMMLSM | R Documentation |

Time-dependent AUC for joint models

```
AUCJMMLSM(
object,
seed = 100,
landmark.time = NULL,
horizon.time = NULL,
obs.time = NULL,
method = c("Laplace", "GH"),
quadpoint = NULL,
maxiter = 1000,
n.cv = 3,
survinitial = TRUE,
...
)
```

`object` |
object of class 'JMMLSM'. |

`seed` |
a numeric value of seed to be specified for cross validation. |

`landmark.time` |
a numeric value of time for which dynamic prediction starts.. |

`horizon.time` |
a numeric vector of future times for which predicted probabilities are to be computed. |

`obs.time` |
a character string of specifying a longitudinal time variable. |

`method` |
estimation method for predicted probabilities. If |

`quadpoint` |
the number of pseudo-adaptive Gauss-Hermite quadrature points if |

`maxiter` |
the maximum number of iterations of the EM algorithm that the function will perform. Default is 10000. |

`n.cv` |
number of folds for cross validation. Default is 3. |

`survinitial` |
Fit a Cox model to obtain initial values of the parameter estimates. Default is TRUE. |

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

a list of matrices with conditional probabilities for subjects.

Shanpeng Li lishanpeng0913@ucla.edu

`JMMLSM, survfitJMMLSM`

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