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A Nonparametric Least-Squares Estimation Method for Tumor Growth Function with Interval-Censored Observation
| Content Provider | Semantic Scholar |
|---|---|
| Author | Cheng, Gang Zhang, Ying Li-Qiang, Lu |
| Copyright Year | 2013 |
| Abstract | Study of tumor growth is an important area in cancer research. In this manuscript, we propose a nonparametric least-squares method to estimate tumor growth function for the case that tumor onset time is subject to interval censoring. Such scenarios constantly arise in animal tumorigenicity experiments and tumor screening programs, in which tumor onset time is only known within an interval made by adjacent screening times. The proposed estimator is shown asymptotically consistent under a specific metric using modern empirical process theory. Simulation studies are carried out to justify validity of the proposed method. Finally the method is applied to estimate breast tumor growth for the cohort of breast cancer patients in the state of Iowa of the United States using the data extracted from the Surveillance, Epidemiology and End Results (SEER) program. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://cph.uiowa.edu/biostat/research/documents/Cheng-Zhang%20Biometrika_plain.pdf |
| Alternate Webpage(s) | http://www.public-health.uiowa.edu/biostat/research/documents/Cheng-Zhang%20Biometrika_plain.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
