Master of Science / Department of Statistics / Gary Gadbury / This report illustrates how to use two statistic methods to investigate the performance of a new technique to detect breast cancer and lung cancer at early stages. The two methods include logistic regression and classification and regression tree (CART). It is found that the technique is effective in detecting breast cancer and lung cancer, with both sensitivity and specificity close to 0.9. But the ability of this technique to predict the actual stages of cancer is low. The age variable improves the ability of logistic regression in predicting the existence of breast cancer for the samples used in this report. But since the sample sizes are small, it is impossible to conclude that including the age variable helps the prediction of breast cancer. Including the age variable does not improve the ability to predict the existence of lung cancer. If the age variable is excluded, CART and logistic regression give a very close result.
| Identifer | oai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/16679 |
| Date | January 1900 |
| Creators | Sun, Xin |
| Publisher | Kansas State University |
| Source Sets | K-State Research Exchange |
| Language | en_US |
| Detected Language | English |
| Type | Report |
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