frailtypack: An R Package for the Analysis of Correlated Survival Data with Frailty Models Using Penalized Likelihood Estimation or Parametrical Estimation

被引：0
作者：
Rondeau, Virginie [1 ]
Mazroui, Yassin [1 ]
Gonzalez, Juan R. [2 ]
机构：
[1] Univ Bordeaux Segalen, Bordeaux, France
[2] CREAL Ctr Res Environm Epidemiol, Barcelona 08003, Spain
来源：
JOURNAL OF STATISTICAL SOFTWARE | 2012年 / 47卷 / 04期
关键词：
frailty models; R; penalized likelihood; Marquardt; cross-validation; correlated survival data; splines; hazard functions; PROPORTIONAL HAZARDS MODEL; HETEROGENEITY; ALGORITHM;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Frailty models are very useful for analysing correlated survival data, when observations are clustered into groups or for recurrent events. The aim of this article is to present the new version of an R package called frailtypack. This package allows to fit Cox models and four types of frailty models (shared, nested, joint, additive) that could be useful for several issues within biomedical research. It is well adapted to the analysis of recurrent events such as cancer relapses and/or terminal events (death or lost to follow-up). The approach uses maximum penalized likelihood estimation. Right-censored or left-truncated data are considered. It also allows stratification and time-dependent covariates during analysis
引用
收藏
页码：1 / 28
页数：28
相关论文
共 26 条
[11]   A penalized likelihood approach for arbitrarily censored and truncated data: Application to age-specific incidence of dementia [J].
Joly, P ;
Commenges, D ;
Letenneur, L .
BIOMETRICS, 1998, 54 (01) :185-194
[12]   SEMIPARAMETRIC ESTIMATION OF RANDOM EFFECTS USING THE COX MODEL BASED ON THE EM ALGORITHM [J].
KLEIN, JP .
BIOMETRICS, 1992, 48 (03) :795-806
[13]   A Bayesian approach to jointly estimate centre and treatment by centre heterogeneity in a proportional hazards model [J].
Legrand, C ;
Ducrocq, V ;
Janssen, P ;
Sylvester, R ;
Duchateau, L .
STATISTICS IN MEDICINE, 2005, 24 (24) :3789-3804
[14]   AN ALGORITHM FOR LEAST-SQUARES ESTIMATION OF NONLINEAR PARAMETERS [J].
MARQUARDT, DW .
JOURNAL OF THE SOCIETY FOR INDUSTRIAL AND APPLIED MATHEMATICS, 1963, 11 (02) :431-441
[15]   Likelihood ratio, score, and Wald tests in a constrained parameter space [J].
Molenberghs, Geert ;
Verbeke, Geert .
AMERICAN STATISTICIAN, 2007, 61 (01) :22-27
[16]   FAST COMPUTATION OF FULLY AUTOMATED LOG-DENSITY AND LOG-HAZARD ESTIMATORS [J].
OSULLIVAN, F .
SIAM JOURNAL ON SCIENTIFIC AND STATISTICAL COMPUTING, 1988, 9 (02) :363-379
[17]  
POPE CA, 1995, AM J RESP CRIT CARE, V151, P669, DOI 10.1164/ajrccm/151.3_Pt_1.669
[18]   Investigating trial and treatment heterogeneity in an individual patient data meta-analysis of survival data by means of the penalized maximum likelihood approach [J].
Rondeau, V. ;
Michiels, S. ;
Liquet, B. ;
Pignon, J. P. .
STATISTICS IN MEDICINE, 2008, 27 (11) :1894-1910
[19]   Nested frailty models using maximum penalized likelihood estimation [J].
Rondeau, V. ;
Filleul, L. ;
Joly, P. .
STATISTICS IN MEDICINE, 2006, 25 (23) :4036-4052
[20]   frailtypack:: A computer program for the analysis of correlated failure time data using penalized likelihood estimation [J].
Rondeau, V ;
Gonzalez, JR .
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2005, 80 (02) :154-164
123