Varphi_par: \varphi

Description Usage Arguments Details References

View source: R/Varphi_par.R

\varphi

Description

This function computes varphi_k(t;z_0).

Usage

1
Varphi_par(est, x, y, kk, CIFest, data, newdata, group, event, save, group.in.train)

Arguments

est

The model fitting details from the k^th cause-specific hazards model.

x

The design matrix associated with the k^th type of failure, of dimension n observations * p_k covariates.

y

The survival response associated with the k^th type of failure.

kk

The k^th type of failure.

CIFest

(Internal) The point estimator of the cumulative incidence function.

data

A data frame with n observations and p number of covariates.

newdata

A data frame or a matrix used for prediction. If not specified, the original data will be used instead.

group

The name of the group covariates (if any). If specified, the cumulative hazards will be estimated for each group seperately. Default is group=NULL.

event

This is an internal binary indicator to specify if any type of failure occurs at a given time.

save

An option to save the computed S0 and S1. It is highly recommended for large-scale dataset to improve the computational efficiency. Default is save=FALSE.

group.in.train

This argument is valid only when the group argument is specified. If group is presented in both data and newdata, use group.in.train=T. If group is presented in only newdata but not data, use group.in.train=F.

Details

This function computes

\hat{\varphi}_{k}(t; z_{0}) = \frac{1}{n}∑_{i=1}^{n}\hat{S}(\tilde{T}_{i}; z_{0})(z_{0}- \bar{Z}(\hat{β}_{k}, \tilde{T_{i}}))\frac{\exp(\hat{β}_{k}^{T}z_{0})δ_{ji}I(\tilde{T}_{i} ≤ t)}{S^{(0)}(\hat{β}_{k}, \tilde{T}_{i})}

References

Cheng, S. C., Jason P. Fine, and L. J. Wei. "Prediction of cumulative incidence function under the proportional hazards model." Biometrics (1998): 219-228.


CompetingRisk documentation built on May 30, 2017, 2:54 a.m.