Coxwt: Weighted Cox PH model estimation

In SurvMI: Multiple Imputation Method in Survival Analysis

Description

Estimate the Cox PH model by weighted partial likelihood. Event weights are calcualted with respect to event probabilities.

Usage

Coxwt(data_list,covariates,init=NULL,BS=FALSE,nBS=1000)

Arguments

data_list	The data list which has been transformed from the long format by the uc_data_transform function.
covariates	The vector of varaible on the RHS of the Cox model.
init	The initial value of covariates vector in the likelihood, length matches the length of covariates.
BS	T/F, whether conduct estimation via the Bootstrap method.
nBS	Number of BS, only effective if BS=TRUE.

Value

coefficients	Estimated vector of coefficients in the model
var	Estimated variance of the coefficients
hr	Estimated hazard ratios in the model
z	Wald test statistics
pvalue	Estimated two-sided p-value
coefficients_bs	Bootstrapped coefficient estimation
var_bs	Bootstrapped variance estimation
column_name	Column name

Author(s)

Yiming Chen, John Lawrence

References

[1]Cook TD. Adjusting survival analysis for the presence of unadjudicated study events. Controlled clinical trials. 2000;21(3):208-222.

[2]Cook TD, Kosorok MR. Analysis of time-to-event data with incomplete event adjudication. Journal of the american statistical association. 2004;99(468):1140-1152.

[3]Snapinn SM. Survival analysis with uncertain endpoints. Biometrics. 1998;54(1):209-218.

See Also

CoxMI, Coxwt.summ.

Examples

df_x<-data_sim(n=500,0.8,haz_c=0.5/365)
data_intrim<-uc_data_transform(data=df_x,
                               var_list=c("id_long","trt_long"),
                               var_list_new=c("id","trt"),
                               time="time_long",
                               prob="prob_long")
 fit<-Coxwt(data_list=data_intrim,covariates=c("trt"),init=c(1),BS=FALSE)
 Coxwt.summ(fit)

##an example if we would like to check the BS variance

fit2<-Coxwt(data_list=data_intrim,covariates=c("trt"),init=c(1),BS=TRUE, nBS = 100)
Coxwt.summ(fit2)

SurvMI documentation built on July 13, 2020, 9:07 a.m.