lambda_j_Exp {eventTrack}

Compute lambda_j

Description

For given change points \tau_1, \ldots, \tau_k, compute the profile maximum likelihood estimates \lambda_1, \ldots, \lambda_{k + 1} for the values of the piecewise constant hazard function in a piecewise Exponential survival model. Standard errors for these estimates are provided as well, based on standard maximum (profile) maximum likelihood theory.

Usage

lambda_j_Exp(tau, time, event)

Arguments

tau

Single number or vector with values of change points.

time

Event times, censored or observed, in months.

event

Censoring indicator, 1 for event, 0 for censored.

Value

A list containing the following elements:

aj

The esimtates of the \lambda_j.

hess.diag

The diagonal of the corresponding Hessian matrix. Note that the off-diagonal elements of the Hessian are all equal to 0.

Note

This function is not intended to be invoked by the end user.

Author(s)

Kaspar Rufibach (maintainer)
[e-mail]

References

Fang, L., Zheng, S. (2011). A hybrid approach to predicting events in clinical trials with time-to-event outcomes. Contemp. Clin. Trials, 32, 755–759.

Goodman, M.S., Li, Y., Tiwari, R.C. (2011). Detecting multiple change points in piecewise constant hazard functions. J. Appl. Stat, 38(11), 2523–2532.