Change point estimation in monitoring survival time: probability of the occurrence of the change point in the last {25, 50, 100, 200, 300, 400, 500} observations prior to signalling for RAST CUSUM
Viewed:
1986
The dataset was collected to model change point estimation in time-to-event data for a clinical process with dichotomous outcomes, death and survival, where patient mix was present. Modelling was completed using a Bayesian framework. The performance of the Bayesian estimators was investigated through simulation in conjunction with RAST CUSUM control charts for monitoring right censored survival time of patients who underwent cardiac surgery procedures within a follow-up period of 30 days.
The dataset presents the probability of the occurrence of the change point in the last {25, 50, 100, 200, 300, 400, 500} observations prior to signalling for RAST CUSUM () where and .
Geographical area of data collection
kmlPolyCoords
153.552920,-26.777500 152.452799,-26.777500 152.452799,-28.037280 153.552920,-28.037280 153.552920,-26.777500
Publications
Assareh, Hassan & Mengersen, Kerrie (2012) Change Point Estimation in Monitoring Survival Time. PLoS ONE, 7(3), e33630.
http://dx.doi.org/10.1371/journal.pone.0033630
Research areas
Signals
Markov models
Monte Carlo method
Estimator
Racusum
MATHEMATICAL
SCIENCES
Data processing
Biotechnology
Cardiac surgery
Information
and
computing
sciences
Bayesian
Bayes theorem
Death rates
Charts
Cusum
Surgical and invasive medical procedures
Cite this collection
Assareh, Hassan ; Mengersen, Kerrie (2014): Change point estimation in monitoring survival time: probability of the occurrence of the change point in the last {25, 50, 100, 200, 300, 400, 500} observations prior to signalling for RAST CUSUM. Queensland University of Technology. (Dataset) https://doi.org/10.4225/09/58576258385db
Related information
Hassan Assareh, former research officer, QUT - collaborator
http://eprints.qut.edu.au/view/person/Assareh,_Hassan.html
The study was supported by Queensland University of Technology and St. Andrew's Medical Institute, Brisbane, Australia, through an ARC linkage.
https://doi.org/10.1371/journal.pone.0033630
Access the data
Data file types
.csv
Licence
Copyright
Copyright: © 2012 Assareh, Mengersen.
Dates of data collection
From 2012-01-01 to 2012-12-31
Contacts
Name: Distinguished Professor Kerrie Mengersen
Email: kerrie.mengersen@qut.edu.au
Phone: +61 7 3138 2063
Other
Date record created:
2014-10-16T17:36:47
Date record modified:
2019-08-15T14:00:20
Record status:
Published - Open Access