Work

SurvImpute: Multiple Imputation for Missing Covariates in Time-to-Event Data

Year: 2025

Type: dataset

Abstract: Generates multiple imputed datasets from a substantive model compatible fully conditional specification model for time-to-event data. Our method assumes that the censoring process also depends on the covariates with missing values. Details will be available in an upcoming publication.

DOI: 10.32614/cran.package.survimpute

Authors: Qinghua Lian, Soyoung Kim, Michael J. Martens, Kwang Woo Ahn

Language: English

Topic: Statistical Methods and Bayesian Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

OpenAlex ID: W4407023352

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