Description Usage Arguments Details Value Author(s) References See Also Examples

Fit mixture cure models with random effects based on numerical integration.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ```
intcure(
formula = formula(data),
cureform = NULL,
data = sys.parent(),
subset,
na.action,
bt = NULL,
gm = NULL,
basepara = NULL,
sigma = c(0, 0, 0),
optimcfg = list(ndeps = 0.001, maxit = 1000, reltol = 1e-05, method = "Nelder-Mead",
hessian = FALSE),
intcfg = list(eps = 1e-04, lower = c(-5, -5), upper = c(5, 5)),
basedist = c("exponential", "weibull", "piecewise"),
npiece = 3,
piececut = NULL,
piececuttype = c("quantile", "even"),
model = FALSE,
y = TRUE,
x = FALSE,
z = FALSE,
funval = FALSE,
debug = c("intcure", "integration", "optim")
)
``` |

`formula` |
a formula expression similar to the one used in |

`cureform` |
a formula expression similar to formula except that
it does not contain a response. It is used to specify the effects
of covariates on the cure rate. A covariate that defines clusters
in data will be in |

`data, subset, na.action` |
standard arguments for R model functions |

`bt` |
a vector of initial value of beta in the latency model.
It is optional. If |

`gm` |
a vector of initial value of gamma in the incidence model. It is optional |

`basepara` |
a vector of initial values of the parameters in the baseline
distribution. They are the log rate if baseline = |

`sigma` |
a vector of 3 corresponding to log standard deviation of u and v,
and a Fisher's z-transformed correlation coefficient of u and v.
If any of the value is set to |

`optimcfg` |
a list of |

`intcfg` |
a list of |

`basedist` |
type of baseline distribution. It can be one of |

`npiece, piececut, piececuttype` |
arguments for baseline distribution
when it is piecewise constant hazard distribution. They are respectively
the number of pieces, the cut points to form the pieces and how the pieces
are formed. |

`model` |
if TRUE, output model matrix instead of fitting the model |

`y, x, z` |
if TRUE, output corresponding matrix in the model matrix |

`funval` |
a logical value. If TRUE, evaluate the likelihood function at initial values instead of fitting the model |

`debug` |
for debug purpose |

This package depends on `cubature`

package for numerical
integration and `mvtnorm`

package. Better initial values for `bt`

,
`gm`

and `basepara`

obtained
from a mixture cure model without random effects may help speed up the
program or finding the best estimates.

an object of class `intcure`

is returned. It includes all the values
returned from `optim()`

in addition to the following values:

`call` |
The call to |

`basedist` |
The baseline distribution fitted |

`method` |
The optimization method used |

`n` |
Sample size |

Yingwei Peng

Peng, Y. and Taylor, J. M. G. Mixture cure model with random effects for the analysis of a multi-centre tonsil cancer study. Statistics in Medicine, 30:211-223, 2011

1 2 3 |

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.