This function computes the predicted cumulative incidence of each cause of event according to a profile of covariates from a joint latent class model. Confidence bands can be computed by a Monte-Carlo method.

1 |

`x` |
an object inheriting from class |

`time` |
a vector of times at which the cumulative incidence is calculated |

`draws` |
optional boolean specifying whether a Monte Carlo approximation of the posterior distribution of the cumulative incidence is computed and the median, 2.5% and 97.5% percentiles are given. Otherwise, the predicted cumulative incidence is computed at the point estimate. By default, draws=FALSE. |

`ndraws` |
if draws=TRUE, ndraws specifies the number of draws that should be generated to approximate the posterior distribution of the predicted cumulative incidence. By default, ndraws=2000. |

`...` |
further arguments, in particular values of the covariates specified in the survival part of the joint model. |

An object of class `cuminc`

containing as many matrices as profiles defined by the covariates
values. Each of these matrices contains the event-specific cumulative incidences in
each latent class at the different times specified.

Viviane Philipps and Cecile Proust-Lima

`Jointlcmm`

,`plot.Jointlcmm`

,`plot.cuminc`

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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