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SurvMI (version 0.1.0)

Multiple Imputation Method in Survival Analysis

Description

In clinical trials, endpoints are sometimes evaluated with uncertainty. Adjudication is commonly adopted to ensure the study integrity. We propose to use multiple imputation (MI) introduced by Robin (1987) to incorporate these uncertainties if reasonable event probabilities were provided. The method has been applied to Cox Proportional Hazard (PH) model, Kaplan-Meier (KM) estimation and Log-rank test in this package. Moreover, weighted estimations discussed in Cook (2004) were also implemented with weights calculated from event probabilities. In conclusion, this package can handle time-to-event analysis if events presented with uncertainty by different methods.

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Version

Install

install.packages('SurvMI')

Monthly Downloads

180

Version

0.1.0

License

GPL-2

Maintainer

Yiming Chen

Last Published

July 13th, 2020

Functions in SurvMI (0.1.0)

CoxMI.summ

Summary function for the Cox MI model
Coxwt

Weighted Cox PH model estimation
Coxwt.summ

Summary function for the weighted Cox model
LRMI

Log-rank test with events uncertainty
uc_data_transform

Transform long formatted time-to-event data into a data list
LRMI.summ

Prints the test results output by the LRMI function
data_sim

Simulated survival data with uncertain endpoints from exponential distribution.
KMMI

Kaplan-Meier estimation with event uncertainty
CoxMI

Cox PH model with MI method