Sensitivity analysis of predictive modeling for responses from the three-parameter Weibull model with a follow-up doubly censored sample of cancer patients
AbstractThe purpose of this paper is to derive the predictive densities for future responses from the three-parameter Weibull model given a doubly censored sample. The predictive density for a single future response, bivariate future response, and a set of future responses has been derived when the shape parameter [alpha] is unknown. A real data example representing 44 patients who were diagnosed with laryngeal cancer (2000-2007) at a local hospital is used to illustrate the predictive results for the four stages of cancer. The survival days of eight out of the 44 patients could not be calculated as the patients were lost to follow-up. They were the first four and the last four patients' survival days in order. Thus, the recorded data for the survival days of 36 patients composed of 18 male and 18 female patients with cancer of the larynx are used for the predictive analysis. Furthermore, a subgroup level of the male and female patients follow-up data are considered to obtain the future survival days. A sensitivity study of the mean, standard deviation, and 95% highest predictive density (HPD) interval of the future survival days with respect to stages and doses are performed when the shape parameter [alpha] is unknown.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 55 (2011)
Issue (Month): 12 (December)
Contact details of provider:
Web page: http://www.elsevier.com/locate/csda
Censored sample Doubly censored sample Three-parameter Weibull model Bayesian approach Predictive inference;
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- BuHamra, Sana S. & Al-Kandari, N.M.Noriah M. & Ahmed, S. E., 2004. "Inference concerning quantile for left truncated and right censored data," Computational Statistics & Data Analysis, Elsevier, vol. 46(4), pages 819-831, July.
- Fernández, Arturo J. & Pérez-González, Carlos J., 2012. "Optimal acceptance sampling plans for log-location–scale lifetime models using average risks," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 719-731.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.