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

M-spline estimate of the transition intensity function and the cumulative transition intensity function for survival and illness-death models

1 |

`times` |
Time points at which to estimate the intensity function |

`knots` |
Knots for the M-spline |

`number.knots` |
Number of knots for the M-splines (and I-splines see details) |

`theta` |
The coefficients for the linear combination of M-splines (and I-splines see details) |

`linear.predictor` |
Linear predictor beta*Z. When it is non-zero,
transition and cumulative transition are multiplied by |

The estimate of the transition intensity function is a linear
combination of M-splines and the estimate of the cumulative transition
intensity function is a linear combination of I-splines (the integral of a
M-spline is called I-spline). The coefficients `theta`

are the same for
the M-splines and I-splines.

Important: the theta parameters returned by `idm`

and `shr`

are in fact
the square root of the splines coefficients. See examples.

This function is a R-translation of a corresponding Fortran function called `susp`

. `susp`

is
used internally by `idm`

and `shr`

.

`times` |
The time points at which the following estimates are evaluated. |

`intensity` |
The transition intensity function evaluated at |

`cumulative.intensity` |
The cumulative transition intensity function evaluated at |

`survival` |
The "survival" function, i.e., exp(-cumulative.intensity) |

R: Celia Touraine <Celia.Touraine@isped.u-bordeaux2.fr> and Thomas Alexander Gerds <tag@biostat.ku.dk> Fortran: Pierre Joly <Pierre.Joly@isped.u-bordeaux2.fr>

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | ```
data(testdata)
fit.su <- shr(Hist(time=list(l, r), id) ~ cov,
data = testdata,method = "Splines",CV = TRUE)
intensity(times = fit.su$time, knots = fit.su$knots,
number.knots = fit.su$nknots, theta = fit.su$theta^2)
## Not run:
data(Paq1000)
fit.idm <- idm(formula02 = Hist(time = t, event = death, entry = e) ~ certif,
formula01 = Hist(time = list(l,r), event = dementia) ~ certif,
formula12 = ~ certif, method = "Splines", data = Paq1000)
# Probability of survival in state 0 at age 80 for a subject with no cep given
that he is in state 0 at 70
su0 <- (intensity(times = 80, knots = fit.idm$knots01,
number.knots = fit.idm$nknots01,
theta = fit.idm$theta01^2)$survival
*intensity(times = 80, knots = fit.idm$knots02,
number.knots = fit.idm$nknots02,
theta = fit.idm$theta02^2)$survival)/
(intensity(times = 70, knots = fit.idm$knots01,
number.knots = fit.idm$nknots01,
theta = fit.idm$theta01^2)$survival
*intensity(times = 70, knots = fit.idm$knots02,
number.knots = fit.idm$nknots02,
theta = fit.idm$theta02^2)$survival)
# Same result as:
predict(fit.idm, s = 70, t = 80, conf.int = FALSE) # see first element
## End(Not run)
``` |

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.