Statistical modeling of lung cancer: answering relative questions.

THE OBJECTIVE OF THIS PAPER IS TO PERFORM PARAMETRIC AND NONPARAMETRIC ANALYSIS TO ADDRESS SOME VERY IMPORTANT QUESTIONS CONCERNING LUNG CANCER UTILIZING REAL LUNG CANCER DATA

What is the probabilistic nature of mortality time in ex-smoker lung cancer patients and non-smoker lung cancer patients, for female, male, and the totality of female and male patients? Is there significant difference of mortality time between ex-smoker and non-smoker patients? For ex-smokers, are there any differences with respect to the key variables such as mortality time, cigarettes per day (CPD), and duration of smoking between female and male patients? For non-smokers, can we notice a difference in mortality time between female and male patients? Can we accurately predict mortality time given information on CPD, starting time and quitting time for a specific lung cancer patient who smokes? Thus best fitting probability distributions are identified and their parameters are estimated. Mean mortality times are compared between non-smokers and ex-smokers, female non-smokers and male non-smokers, and female ex-smokers and male ex-smokers. Important entities related to lung cancer mortality time, such as cigarettes per day (CPD), and duration of smoking (DUR), are compared between female and male ex-smoker lung cancer patients. Finally, a model is developed to predict the mortality time of ex-smokers with a high degree of accuracy.