Quantile function regression analysis for interval censored data, with application to salary survey data

Author(s):  
Chih-Yuan Hsu ◽  
Chi-Chung Wen ◽  
Yi-Hau Chen
Biometrics ◽  
2021 ◽  
Author(s):  
Liuquan Sun ◽  
Shuwei Li ◽  
Lianming Wang ◽  
Xinyuan Song ◽  
Xuemei Sui

2019 ◽  
Vol 29 (3) ◽  
pp. 752-764 ◽  
Author(s):  
Camille Sabathé ◽  
Per K Andersen ◽  
Catherine Helmer ◽  
Thomas A Gerds ◽  
Hélène Jacqmin-Gadda ◽  
...  

Pseudo-values provide a method to perform regression analysis for complex quantities with right-censored data. A further complication, interval-censored data, appears when events such as dementia are studied in an epidemiological cohort. We propose an extension of the pseudo-value approach for interval-censored data based on a semi-parametric estimator computed using penalised likelihood and splines. This estimator takes interval-censoring and competing risks into account in an illness-death model. We apply the pseudo-value approach to three mean value parameters of interest in studies of dementia: the probability of staying alive and non-demented, the restricted mean survival time without dementia and the absolute risk of dementia. Simulation studies are conducted to examine properties of pseudo-values based on this semi-parametric estimator. The method is applied to the French cohort PAQUID, which included more than 3,000 non-demented subjects, followed for dementia for more than 25 years.


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