Award Date

5-2011

Degree Type

Thesis

Degree Name

Master of Science in Mathematical Science

Department

Mathematical Sciences

First Committee Member

Chih-Hsiang Ho, Chair

Second Committee Member

Anton Westveld

Third Committee Member

Amei Amei

Graduate Faculty Representative

Chad Cross

Number of Pages

68

Abstract

Leukemia related deaths increased dramatically over the last forty years. Leukemia is a malignant disease or cancer of the bone marrow and blood. It is characterized by the uncontrolled accumulation of blood cells. Leukemia is divided into two categories: myelogenous or lymphocytic, each of which can be acute or chronic. The terms, myelogenous or lymphocytic denote the cell type involved.

In this thesis, the proposed modeling techniques are applied to leukemia deaths data from the Surveillance Epidemiology and End Results (SEER). In particular, annual deaths data from 1969 to 2007 are used in the data analysis, which includes three major parts: 1) male and female death rate comparisons using the conditional test (Przyborowski and Wilenski, 1940); 2) development of the empirical recurrence rate (Ho, 2008) and the empirical recurrence rates ratio time series; and 3) the Autoregressive Integrated Moving Average (ARIMA) model: selection, validation, and forecasting for the leukemia death rates and ratio.

Keywords

Autoregressive Integrated Moving Average (ARIMA); Epidemiology; Leukemia – Mortality; Leukemia – Relapse; Mortality — Sex differences; Recurrence; Surveillance Epidemiology and End Results (SEER)

Disciplines

Epidemiology | Mathematics | Oncology | Vital and Health Statistics

Language

English


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