JMcmprsk: An R Package for Joint Modelling of Longitudinal and Survival Data with Competing Risks

被引:0
|
作者
Wang, Hong [1 ]
Li, Ning [2 ]
Li, Shanpeng [3 ]
Li, Gang [3 ]
机构
[1] Cent South Univ, Sch Math & Stat, Changsha 410075, Hunan, Peoples R China
[2] UCLA Biomath, Los Angeles, CA 90095 USA
[3] Univ Calif Los Angeles, Sch Publ Hlth, Dept Biostat, Los Angeles, CA 90095 USA
来源
R JOURNAL | 2021年 / 13卷 / 01期
关键词
TO-EVENT DATA;
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
In this paper, we describe an R package named JMcmprsk, for joint modelling of longitudinal and survival data with competing risks. The package in its current version implements two joint models of longitudinal and survival data proposed to handle competing risks survival data together with continuous and ordinal longitudinal outcomes respectively (Elashoff et al., 2008; Li et al., 2010). The corresponding R implementations are further illustrated with real examples. The package also provides simulation functions to simulate datasets for joint modelling with continuous or ordinal outcomes under the competing risks scenario, which provide useful tools to validate and evaluate new joint modelling methods.
引用
收藏
页码:53 / 68
页数:16
相关论文
共 50 条
  • [1] Joint modelling of longitudinal and competing risks data
    Williamson, P. R.
    Kolamunnage-Dona, R.
    Philipson, R.
    Marson, A. G.
    [J]. STATISTICS IN MEDICINE, 2008, 27 (30) : 6426 - 6438
  • [2] Joint modelling of longitudinal and survival data in the presence of competing risks with applications to prostate cancer data
    Sheikh, Md Tuhin
    Ibrahim, Joseph G.
    Gelfond, Jonathan A.
    Sun, Wei
    Chen, Ming-Hui
    [J]. STATISTICAL MODELLING, 2021, 21 (1-2) : 72 - 94
  • [3] JOINT MODELLING OF LONGITUDINAL AND COMPETING RISKS DATA IN CLINICAL RESEARCH
    Teixeira, Laetitia
    Sousa, Ines
    Rodrigues, Anabela
    Mendonca, Denisa
    [J]. REVSTAT-STATISTICAL JOURNAL, 2019, 17 (02) : 245 - 264
  • [4] Assessing importance of biomarkers: A Bayesian joint modelling approach of longitudinal and survival data with semi-competing risks
    Zhang, Fan
    Chen, Ming-Hui
    Cong, Xiuyu Julie
    Chen, Qingxia
    [J]. STATISTICAL MODELLING, 2021, 21 (1-2) : 30 - 55
  • [5] Joint Inference for Competing Risks Survival Data
    Li, Gang
    Yang, Qing
    [J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2016, 111 (515) : 1289 - 1300
  • [6] JM: An R Package for the Joint Modelling of Longitudinal and Time-to-Event Data
    Rizopoulos, Dimitris
    [J]. JOURNAL OF STATISTICAL SOFTWARE, 2010, 35 (09): : 1 - 33
  • [7] A joint model of longitudinal and competing risks survival data with heterogeneous random effects and outlying longitudinal measurements
    Huang, Xin
    Li, Gang
    Elashoff, Robert M.
    [J]. STATISTICS AND ITS INTERFACE, 2010, 3 (02) : 185 - 195
  • [8] A Joint Frailty Model for Competing Risks Survival Data
    Ha, Il Do
    Cho, Geon-Ho
    [J]. KOREAN JOURNAL OF APPLIED STATISTICS, 2015, 28 (06) : 1209 - 1216
  • [9] A general joint model for longitudinal measurements and competing risks survival data with heterogeneous random effects
    Xin Huang
    Gang Li
    Robert M. Elashoff
    Jianxin Pan
    [J]. Lifetime Data Analysis, 2011, 17 : 80 - 100
  • [10] A general joint model for longitudinal measurements and competing risks survival data with heterogeneous random effects
    Huang, Xin
    Li, Gang
    Elashoff, Robert M.
    Pan, Jianxin
    [J]. LIFETIME DATA ANALYSIS, 2011, 17 (01) : 80 - 100