April 24, 2014 -
11:00 am to 12:00 pm
Location: Cupples I, Room 215 |
Host: Prof. Jiming Ding
A Master in Statistics Thesis Defense
Abstract:Alzheimer's Disease (AD) is a serious disease which is frequently in the news nowadays. Almost 1/3 of elderly people have this disease. Some biological factors are found to be associated with it, such as gender, age and education level. The governments all over the world have paid a large amount of money to solve this problem, but the result is not as good as people expected. AD cannot be cured at this time. To find as soon as possible whether a person has AD is the best way to control AD. My goal in this thesis is to describe some models to help discover the presence of AD in clinical trials. The original data is collected by OASIS (Open Access Series of Imaging Studies). We have about 400 subjects in this research. Due to some problems about protection, only 235 subjects have provided the entire information. I will consider these 235 subjects in this thesis, and 100 of them have AD. To analyze the image data of AD in the brain, the high dimension of the image is the most important problem that should be solved. Principal Component Analysis (PCA) and wavelet transformation are the two popular methods to solve this problem. I will do Logistic Regression based on PCA to consider whether a person has AD as the predicted variable in the first part. And I will use the functional linear model to consider the wavelet coefficients as the predicted variables in the second part. Finally, I will discuss the advantages and disadvantages of these analysis methods.
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