Parametric inference with density-free variance in censored regression models
| dc.creator | Hummer, Amanda J. | |
| dc.date.accessioned | 2016-11-14T23:08:58Z | |
| dc.date.available | 2011-02-18T23:20:31Z | |
| dc.date.available | 2016-11-14T23:08:58Z | |
| dc.date.issued | 2000-05 | |
| dc.degree.department | Statistics | en_US |
| dc.description.abstract | Survival analysis describes the analysis of data that corresponds to the time from a well-defined time origin until the occurrence of the some particular event, the endpoint. In medical research the time origin may be the time at which the patient is recruited and the end-point may be death or recurrence of symptoms. Often patients are lost to follow-up for some reason. For example, the individual may be relocated after being recruited in a clinical trial, or may have died due to reasons unrelated to the study. For these reasons, survival times are frequently censored. Censoring occurs when the end-point of interest has not been observed for an individual participating in the trial. There are several types of censoring; right censoring, left censoring, interval censoring, etc. Right censoring, the most common type, takes place when the actual survival time is greater than the censored survival time [1]. This happens when the patient died of causes other than those under study, or when the patient withdraws from the study. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/2346/19825 | en_US |
| dc.language.iso | eng | |
| dc.publisher | Texas Tech University | en_US |
| dc.rights.availability | Unrestricted. | |
| dc.subject | Estimation theory | en_US |
| dc.subject | Analysis of covariance | en_US |
| dc.subject | Survival analysis | en_US |
| dc.subject | Regression analysis | en_US |
| dc.title | Parametric inference with density-free variance in censored regression models | |
| dc.type | Thesis |