A new approach for joint modelling of longitudinal measurements and survival times with a cure fraction | Zendy

Song Hui | Zendy; Peng Yingwei | Zendy; Tu Dongsheng | Zendy

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A new approach for joint modelling of longitudinal measurements and survival times with a cure fraction

Author(s) -

Song Hui,

Peng Yingwei,

Tu Dongsheng

Publication year - 2012

Publication title -

canadian journal of statistics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.804

H-Index - 51

eISSN - 1708-945X

pISSN - 0319-5724

DOI - 10.1002/cjs.11127

Subject(s) - joint (building) , statistical inference , clinical trial , fraction (chemistry) , inference , computer science , statistical model , latent variable , statistics , mixed model , longitudinal data , econometrics , longitudinal study , survival analysis , mathematics , medicine , data mining , artificial intelligence , engineering , architectural engineering , chemistry , organic chemistry

The joint analysis of longitudinal measurements and survival data is useful in clinical trials and other medical studies. In this paper, we consider a joint model which assumes a linear mixed $tt$ model for longitudinal measurements and a promotion time cure model for survival data and links these two models through a latent variable. A semiparametric inference procedure with an EM algorithm implementation is developed for the parameters in the joint model. The proposed procedure is evaluated in a simulation study and applied to analyze the quality of life and time to recurrence data from a clinical trial on women with early breast cancer. The Canadian Journal of Statistics 40: 207–224; 2012 © 2012 Statistical Society of Canada

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