Unfolding pathway of myoglobin. Evidence for a multistate process

Biochemistry ◽  
1983 ◽  
Vol 22 (18) ◽  
pp. 4165-4170 ◽  
Author(s):  
Ettore Bismuto ◽  
Giovanni Colonna ◽  
Gaetano Irace
Keyword(s):  
Multistate Process

Quantum Chemical and Theoretical Kinetics Study of the O(3P) + C2H2Reaction:  A Multistate Process†

2006 ◽  
Vol 110 (21) ◽  
pp. 6696-6706 ◽  
Author(s):  
Thanh Lam Nguyen ◽  
Luc Vereecken ◽  
Jozef Peeters
Keyword(s):  
Quantum Chemical ◽  
Kinetics Study ◽  
Multistate Process

scholarly journals Two-Stage Joint Model for Multivariate Longitudinal and Multistate Processes, with Application to Renal Transplantation Data

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Behnaz Alafchi ◽  
Hossein Mahjub ◽  
Leili Tapak ◽  
Ghodratollah Roshanaei ◽  
Mohammad Ali Amirzargar
Keyword(s):  
Renal Transplantation ◽  
Joint Modeling ◽  
Joint Model ◽  
Single Event ◽  
Two Stage ◽  
Longitudinal Outcomes ◽  
Proposed Model ◽  
Longitudinal Biomarker ◽  
Multivariate Longitudinal Outcomes ◽  
Multistate Process

In longitudinal studies, clinicians usually collect longitudinal biomarkers’ measurements over time until an event such as recovery, disease relapse, or death occurs. Joint modeling approaches are increasingly used to study the association between one longitudinal and one survival outcome. However, in practice, a patient may experience multiple disease progression events successively. So instead of modeling of a single event, progression of the disease as a multistate process should be modeled. On the other hand, in such studies, multivariate longitudinal outcomes may be collected and their association with the survival process is of interest. In the present study, we applied a joint model of various longitudinal biomarkers and transitions between different health statuses in patients who underwent renal transplantation. The full joint likelihood approaches are faced with the complexities in computation of the likelihood. So, here, we have proposed two-stage modeling of multivariate longitudinal outcomes and multistate conditions to avoid these complexities. The proposed model showed reliable results compared to the joint model in case of joint modeling of univariate longitudinal biomarker and the multistate process.

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