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
  • [21] An approach to joint analysis of longitudinal measurements and competing risks failure time data
    Elashoff, Robert M.
    Li, Gang
    Li, Ning
    [J]. STATISTICS IN MEDICINE, 2007, 26 (14) : 2813 - 2835
  • [22] Joint Modeling of Longitudinal Outcome and Competing Risks: Application to HIV/AIDS Data
    Ghobadi, Khadijeh Najafi
    Mahjub, Hossein
    Poorolajal, Jalal
    Shakiba, Ebrahim
    Khassi, Kaivan
    Roshanaei, Ghodratollah
    [J]. JOURNAL OF RESEARCH IN HEALTH SCIENCES, 2023, 23 (01)
  • [23] Robust Joint Modeling of Longitudinal Measurements and Competing Risks Failure Time Data
    Li, Ning
    Elashoff, Robert M.
    Li, Gang
    [J]. BIOMETRICAL JOURNAL, 2009, 51 (01) : 19 - 30
  • [24] A two-level copula joint model for joint analysis of longitudinal and competing risks data
    Lu, Xiaoming
    Chekouo, Thierry
    Shen, Hua
    de Leon, Alexander R.
    [J]. STATISTICS IN MEDICINE, 2023, : 1909 - 1930
  • [25] A Semiparametric Bayesian Joint Modelling of Skewed Longitudinal and Competing Risks Failure Time Data: With Application to Chronic Kidney Disease
    Ferede, Melkamu Molla
    Mwalili, Samuel
    Dagne, Getachew
    Karanja, Simon
    Hailu, Workagegnehu
    El-Morshedy, Mahmoud
    Al-Bossly, Afrah
    [J]. MATHEMATICS, 2022, 10 (24)
  • [26] Bayesian joint modeling of ordinal longitudinal measurements and competing risks survival data for analysing Tehran Lipid and Glucose Study
    Baghfalaki, Taban
    Kalantari, Shiva
    Ganjali, Mojtaba
    Hadaegh, Farzad
    Pahlavanzadeh, Bagher
    [J]. JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 2020, 30 (04) : 689 - 703
  • [27] Joint analysis of bivariate competing risks survival times and genetic markers data
    Alexander Begun
    [J]. Journal of Human Genetics, 2013, 58 : 694 - 699
  • [28] Joint analysis of bivariate competing risks survival times and genetic markers data
    Begun, Alexander
    [J]. JOURNAL OF HUMAN GENETICS, 2013, 58 (10) : 694 - 699
  • [29] Competing risks in survival data analysis
    Dutz, Almut
    Loeck, Steffen
    [J]. RADIOTHERAPY AND ONCOLOGY, 2019, 130 : 185 - 189
  • [30] Joint Modelling of Survival and Longitudinal Data with Informative Observation Times
    Dai, Hongsheng
    Pan, Jianxin
    [J]. SCANDINAVIAN JOURNAL OF STATISTICS, 2018, 45 (03) : 571 - 589