Time-to-event-response data

2019 ◽  
pp. 95-118
Author(s):  
Christian Ritz ◽  
Signe Marie Jensen ◽  
Daniel Gerhard ◽  
Jens Carl Streibig
2012 ◽  
Vol 2012 ◽  
pp. 1-37 ◽  
Author(s):  
Olli Saarela ◽  
Sangita Kulathinal ◽  
Juha Karvanen

Under cohort sampling designs, additional covariate data are collected on cases of a specific type and a randomly selected subset of noncases, primarily for the purpose of studying associations with a time-to-event response of interest. With such data available, an interest may arise to reuse them for studying associations between the additional covariate data and a secondary non-time-to-event response variable, usually collected for the whole study cohort at the outset of the study. Following earlier literature, we refer to such a situation as secondary analysis. We outline a general conditional likelihood approach for secondary analysis under cohort sampling designs and discuss the specific situations of case-cohort and nested case-control designs. We also review alternative methods based on full likelihood and inverse probability weighting. We compare the alternative methods for secondary analysis in two simulated settings and apply them in a real-data example.


2011 ◽  
Vol 4 (2) ◽  
pp. 8-12
Author(s):  
Leo Alexander T Leo Alexander T ◽  
◽  
Pari Dayal L Pari Dayal L ◽  
Valarmathi S Valarmathi S ◽  
Ponnuraja C Ponnuraja C ◽  
...  

2002 ◽  
Vol 7 (2) ◽  
pp. 3-14 ◽  
Author(s):  
R. Baronas ◽  
J. Christensen ◽  
F. Ivanauskas ◽  
J. Kulys

A mathematical model of amperometric biosensors has been developed. The model bases on non-stationary diffusion equations containing a non-linear term related to Michaelis-Menten kinetic of the enzymatic reaction. The model describes the biosensor response to mixtures of multiple compounds in two regimes of analysis: batch and flow injection. Using computer simulation, large amount of biosensor response data were synthesised for calibration of a biosensor array to be used for characterization of wastewater. The computer simulation was carried out using the finite difference technique.


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