A proportional hazard cure model for ordinal responses by self-modeling regression

In a medical study, patients have various stages of illness. After treatment the patient will be cured or the stage of illness will change. Since there are suitable evidences of a susceptible population by several levels, the authors combine a Self-Modeling ordinal model for the probability of occur...

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Bibliographic Details
Published in:Journal of applied statistics 2018-08, Vol.45 (11), p.2095-2106
Main Authors: Shirazi, Aliakbar Mastani, Pinheiro, Aluisio
Format: Article
Language:English
Subjects:
Computer simulation
Modelling
Monte Carlo method
ordinal response
Proportional hazard model
Regression analysis
Schizophrenia
self-modeling
Statistical analysis
Statistical methods
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Summary:In a medical study, patients have various stages of illness. After treatment the patient will be cured or the stage of illness will change. Since there are suitable evidences of a susceptible population by several levels, the authors combine a Self-Modeling ordinal model for the probability of occurrence of an event with a Cox regression for the time of occurrence of an event. We proposed the use of self-modeling ordinal longitudinal where the conditional cumulative probabilities for a category of an outcome have a relation with shape-invariant model. A simulation study is carried out for justification of the methodology. A schizophrenia illness data are analyzed based on our model to see whether the treatment affects the illness.
ISSN:0266-4763
1360-0532
DOI:10.1080/02664763.2017.1410526