Cancer is a dangerous disease causing the most deaths in the world today and around 550,000 deaths in America per year (American Cancer Society). Larynx cancer data was recorded by Kardaun (1983). The data was collected at a Dutch hospital during 1970 – 1978. Ninety male adults with cancer of larynx were involved into the study. Each patient was divided into one of four groups depending on his or her illness condition. The data also recorded their age, lifetime, and year of entering the research. These are common factors as factors of other cancer data.
The purpose of this thesis is to apply proportional hazard regression model, additive hazard regression model, censored quantiles regression model, and censored linear regression model to analyze the above larynx cancer data and find the best regression model of data by using each method. Comparison and suggestion for which method should be used in specific situation are also made. Some related topics are also mentioned so we can have resource for future study.
Key words: right censoring, proportional risk model, additive risk model, quantiles regression model, linear regression model.
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