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

View source: R/coxed.gam.tvc.R

This function is called by `coxed`

and is not intended to be used by itself.

1 2 |

`cox.model` |
The output from a Cox proportional hazards model estimated
with the |

`newdata` |
An optional data frame in which to look for variables with which to predict. If omitted, the fitted values are used |

`k` |
The number of knots in the GAM smoother. The default is -1, which
employs the |

`coef` |
A vector of new coefficients to replace the |

`b.ind` |
A vector of observation numbers to pass to the estimation sample to construct the a bootstrapped sample with replacement |

`warn` |
If |

This function employs the GAM method of generating expected durations described
in Kropko and Harden (2018). See `coxed.gam`

for details. This code
replicates the code for `cox.gam`

, but works with data whose structure allows time-varying
covariates, and requires using the `time2`

argument of the `Surv`

function.
This function requires the data to be reported as cumulative durations. The GAM model is fit using
the ending times for each interval and using only the non-censored observations. Expected durations
are drawn from this GAM as with `coxed.gam`

.

Returns a list containing the following components:

`exp.dur` | A vector of predicted mean durations for the estimation sample
if `newdata` is omitted, or else for the specified new data. |

`gam.model` | Output from the `gam` function in which the durations
are fit against the exponentiated linear predictors from the Cox model. |

`gam.data` | Fitted values and confidence intervals from the GAM model. |

Jonathan Kropko <jkropko@virginia.edu> and Jeffrey J. Harden <jharden2@nd.edu>

Kropko, J. and Harden, J. J. (2018). Beyond the Hazard Ratio: Generating Expected
Durations from the Cox Proportional Hazards Model. *British Journal of Political Science*
https://doi.org/10.1017/S000712341700045X

1 2 3 4 5 6 7 | ```
bs.surv <- Surv(time = boxsteffensmeier$start, time2 = boxsteffensmeier$te,
event = boxsteffensmeier$cut_hi)
bs.cox <- coxph(bs.surv ~ ec + dem + south + iv, data = boxsteffensmeier, method = "breslow")
summary(bs.cox)
ed <- coxed.gam.tvc(bs.cox)
ed$exp.dur
``` |

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