Recently, in a series of papers, a method based on pseudo-values has been proposed for direct regression modeling of the survival function, the restricted mean and cumulative incidence function with right censored data. The models, once the pseudo-values have been computed, can be fit using standard generalized estimating equation software. Here we present SAS macros and R functions to compute these pseudo-values. We illustrate the use of these routines and show how to obtain regression estimates for a study of bone marrow transplant patients.
Description
SAS and R Functions to Compute Pseudo-values for Censored Data Regression
%0 Journal Article
%1 Klein:2008:Comput-Methods-Programs-Biomed:18199521
%A Klein, J P
%A Gerster, M
%A Andersen, P K
%A Tarima, S
%A Perme, M P
%D 2008
%J Comput Methods Programs Biomed
%K R SurvivalAnalysis gee sas statistics
%N 3
%P 289-300
%R 10.1016/j.cmpb.2007.11.017
%T SAS and R functions to compute pseudo-values for censored data regression.
%U https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2533132/
%V 89
%X Recently, in a series of papers, a method based on pseudo-values has been proposed for direct regression modeling of the survival function, the restricted mean and cumulative incidence function with right censored data. The models, once the pseudo-values have been computed, can be fit using standard generalized estimating equation software. Here we present SAS macros and R functions to compute these pseudo-values. We illustrate the use of these routines and show how to obtain regression estimates for a study of bone marrow transplant patients.
@article{Klein:2008:Comput-Methods-Programs-Biomed:18199521,
abstract = {Recently, in a series of papers, a method based on pseudo-values has been proposed for direct regression modeling of the survival function, the restricted mean and cumulative incidence function with right censored data. The models, once the pseudo-values have been computed, can be fit using standard generalized estimating equation software. Here we present SAS macros and R functions to compute these pseudo-values. We illustrate the use of these routines and show how to obtain regression estimates for a study of bone marrow transplant patients.},
added-at = {2018-09-21T19:14:23.000+0200},
author = {Klein, J P and Gerster, M and Andersen, P K and Tarima, S and Perme, M P},
biburl = {https://www.bibsonomy.org/bibtex/292d4b9ad47fd8b3940ceeda6d9aa70a2/jkd},
description = {SAS and R Functions to Compute Pseudo-values for Censored Data Regression},
doi = {10.1016/j.cmpb.2007.11.017},
interhash = {8fb0c20eee2793b8d2dbe048bd69e7f4},
intrahash = {92d4b9ad47fd8b3940ceeda6d9aa70a2},
journal = {Comput Methods Programs Biomed},
keywords = {R SurvivalAnalysis gee sas statistics},
month = mar,
number = 3,
pages = {289-300},
pmid = {18199521},
timestamp = {2018-09-21T19:14:23.000+0200},
title = {SAS and R functions to compute pseudo-values for censored data regression.},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2533132/},
volume = 89,
year = 2008
}