Jackknife empirical likelihood for smoothed weighted rank regression with censored data
| atmire.migration.oldid | 192 | |
| dc.contributor.advisor | Lu, Xuewen | |
| dc.contributor.advisor | Kopciuk, Karen | |
| dc.contributor.author | Huang, Longlong | |
| dc.date.accessioned | 2012-07-24T20:25:30Z | |
| dc.date.available | 2012-11-13T08:01:18Z | |
| dc.date.issued | 2012-07-24 | |
| dc.date.submitted | 2012 | en |
| dc.description.abstract | Rank regression is a highly-efficient and robust approach to estimate regression coefficients and to make inference in the presence of outlying survival times. Heller (2007) developed a smoothed weighted rank regression function, which is used to estimate the regression parameter vector in an accelerated failure time model with right censored data. This function can be expressed as a U-statistic. However, since inference is based on a normal approximation approach, it could perform poorly when sample sizes are small and censoring rates are high. To increase inference accuracy and robustness, we propose a jackknife empirical likelihood method for the U-statistic obtained from the estimating function of Heller. The jackknife empirical likelihood ratio is shown to be a standard Chi-squared statistic. Simulations were conducted to compare the proposed method with the normal approximation method. As expected, the new method gives better coverage probability for small samples with high censoring rates. The Stanford Heart Transplant Data, Veterans Administration Lung Cancer Data and Multiple Myeloma Data sets are used to illustrate the proposed method. | en_US |
| dc.identifier.citation | Huang, L. (2012). Jackknife empirical likelihood for smoothed weighted rank regression with censored data (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/26689 | en_US |
| dc.identifier.doi | http://dx.doi.org/10.11575/PRISM/26689 | |
| dc.identifier.uri | http://hdl.handle.net/11023/135 | |
| dc.language.iso | eng | |
| dc.publisher.faculty | Graduate Studies | |
| dc.publisher.institution | University of Calgary | en |
| dc.publisher.place | Calgary | en |
| dc.rights | University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. | |
| dc.subject | Statistics | |
| dc.subject.classification | Accelerated failure time model | en_US |
| dc.subject.classification | Chi-squared statistic | en_US |
| dc.subject.classification | Jackknife empirical likelihood | en_US |
| dc.subject.classification | Normal approximation | en_US |
| dc.subject.classification | Outliers and robustness | en_US |
| dc.subject.classification | Right censored data | en_US |
| dc.subject.classification | Smoothed weighted rank estimating function | en_US |
| dc.subject.classification | U-statistics | en_US |
| dc.title | Jackknife empirical likelihood for smoothed weighted rank regression with censored data | |
| dc.type | master thesis | |
| thesis.degree.discipline | Mathematics and Statistics | |
| thesis.degree.grantor | University of Calgary | |
| thesis.degree.name | Master of Science (MSc) | |
| ucalgary.item.requestcopy | true |