A Proportional Odds Model for Regression Analysis of Case I Interval-Censored Data

2016 ◽  
pp. 101-122
Author(s):  
Pooneh Pordeli ◽  
Xuewen Lu
Keyword(s):  
Regression Analysis ◽  
Censored Data ◽  
Proportional Odds Model ◽  
Interval Censored Data ◽  
Proportional Odds ◽  
Interval Censored

Testing the proportional odds model for interval-censored data

2006 ◽  
Vol 13 (1) ◽  
pp. 37-50 ◽  
Author(s):  
Jianguo Sun ◽  
Liuquan Sun ◽  
Chao Zhu
Keyword(s):  
Censored Data ◽  
Proportional Odds Model ◽  
Interval Censored Data ◽  
Proportional Odds ◽  
Interval Censored

Simultaneous variable selection in regression analysis of multivariate interval‐censored data

Biometrics ◽  
2021 ◽  
Author(s):  
Liuquan Sun ◽  
Shuwei Li ◽  
Lianming Wang ◽  
Xinyuan Song ◽  
Xuemei Sui
Keyword(s):  
Regression Analysis ◽  
Variable Selection ◽  
Censored Data ◽  
Interval Censored Data ◽  
Interval Censored

Semi-Parametric Cure Rate Proportional Odds Models with Spatial Frailties for Interval-Censored Data

2019 ◽  
Vol 11 (03n04) ◽  
pp. 1950005
Author(s):  
Yiqi Bao ◽  
Vicente G. Cancho ◽  
Francisco Louzada ◽  
Adriano K. Suzuki
Keyword(s):  
Censored Data ◽  
Real Data ◽  
Interval Censored Data ◽  
Spatial Correlations ◽  
Cure Rate ◽  
Proportional Odds ◽  
Data Set ◽  
Cure Rate Models ◽  
Cure Models ◽  
Interval Censored

In this work, we proposed the semi-parametric cure rate models with independent and dependent spatial frailties. These models extend the proportional odds cure models and allow for spatial correlations by including spatial frailty for the interval censored data setting. Moreover, since these cure models are obtained by considering the occurrence of an event of interest is caused by the presence of any nonobserved risks, we also study the complementary cure model, that is, the cure models are obtained by assuming the occurrence of an event of interest is caused when all of the nonobserved risks are activated. The MCMC method is used in a Bayesian approach for inferential purposes. We conduct an influence diagnostic through the diagnostic measures in order to detect possible influential or extreme observations that can cause distortions on the results of the analysis. Finally, the proposed models are applied to the analysis of a real data set.

scholarly journals Cure rate proportional odds models with spatial frailties for interval-censored data

2017 ◽  
Vol 24 (6) ◽  
pp. 605-625 ◽  
Author(s):  
Bao Yiqi ◽  
Vicente Garibay Cancho ◽  
Francisco Louzada ◽  
Adriano Kamimura Suzuki
Keyword(s):  
Censored Data ◽  
Interval Censored Data ◽  
Cure Rate ◽  
Proportional Odds ◽  
Interval Censored ◽  
Proportional Odds Models
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