The versatility of multi-state models for the analysis of longitudinal data with unobservable features

被引：0
|
作者：
Vernon T. Farewell
Brian D. M. Tom
机构：
[1] Institute of Public Health,MRC Biostatistics Unit
来源：
Lifetime Data Analysis | 2014年 / 20卷
关键词：
Causal inference; Classification uncertainty; Informative missing data; Multi-state models; Time dependent explanatory variables;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Multi-state models provide a convenient statistical framework for a wide variety of medical applications characterized by multiple events and longitudinal data. We illustrate this through four examples. The potential value of the incorporation of unobserved or partially observed states is highlighted. In addition, joint modelling of multiple processes is illustrated with application to potentially informative loss to follow-up, mis-measured or missclassified data and causal inference.
引用
收藏
页码：51 / 75
页数：24
相关论文
共 50 条
  • [1] The versatility of multi-state models for the analysis of longitudinal data with unobservable features
    Farewell, Vernon T.
    Tom, Brian D. M.
    LIFETIME DATA ANALYSIS, 2014, 20 (01) : 51 - 75
  • [2] Progressive multi-state models for informatively incomplete longitudinal data
    Chen, Baojiang
    Yi, Grace Y.
    Cook, Richard J.
    JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2011, 141 (01) : 80 - 93
  • [3] Multi-State Degradation Analysis for A Condition Monitored Device With Unobservable States
    Moghaddass, Ramin
    Zuo, Ming J.
    2012 INTERNATIONAL CONFERENCE ON QUALITY, RELIABILITY, RISK, MAINTENANCE, AND SAFETY ENGINEERING (ICQR2MSE), 2012, : 549 - 554
  • [4] Multi-state models for the analysis of time-to-event data
    Meira-Machado, Luis
    de Una-Alvarez, Jacobo
    Cadarso-Suarez, Carmen
    Andersen, Per K.
    STATISTICAL METHODS IN MEDICAL RESEARCH, 2009, 18 (02) : 195 - 222
  • [5] Joint modelling of longitudinal ordinal and multi-state data
    Alafchi, Behnaz
    Tapak, Leili
    Mahjub, Hossein
    Ghane, Elaheh Talebi
    Roshanaei, Ghodratollah
    STATISTICAL METHODS IN MEDICAL RESEARCH, 2024, 33 (11-12) : 1939 - 1951
  • [6] Modified Weibull multi-state models for the analysis of animal carcinogenicity data
    Nigel Stallard
    Anne Whitehead
    Environmental and Ecological Statistics, 2000, 7 : 117 - 133
  • [7] Modified Weibull multi-state models for the analysis of animal carcinogenicity data
    Stallard, N
    Whitehead, A
    ENVIRONMENTAL AND ECOLOGICAL STATISTICS, 2000, 7 (02) : 117 - 133
  • [8] Multi-state models
    Andersen, PK
    STATISTICAL METHODS IN MEDICAL RESEARCH, 2002, 11 (02) : 89 - 90
  • [9] Boosting multi-state models
    Holger Reulen
    Thomas Kneib
    Lifetime Data Analysis, 2016, 22 : 241 - 262
  • [10] Multi-state models in epidemiology
    Commenges, D
    LIFETIME DATA ANALYSIS, 1999, 5 (04) : 315 - 327
12345