Dissertation/Thesis Abstract

An Introduction to the Cox Proportional Hazards Model and Its Applications to Survival Analysis
by Thompson, Kristina, M.S., Southern Illinois University at Edwardsville, 2014, 37; 1571931
Abstract (Summary)

Statistical modeling of lifetime data, or survival analysis, is studied in many fields, including medicine, information technology and economics. This type of data gives the time to a certain event, such as death in studies of cancer treatment, or time until a computer program crashes. Researchers are often interested in how covariates affect the time to event and wish to determine ways of incorporating such covariates into statistical models. Covariates are explanatory variables that are suspected to affect the lifetime of interest. Lifetime data are typically subject to censoring and this fact needs to be taken into account when choosing the statistical model.

D.R. Cox (1972) proposed a statistical model that can be used to explore the relationship between survival and various covariates and takes censoring into account. This is called the Cox proportional hazards (PH) model. In particular, the model will be presented and estimation procedures for parameters and functions of interest will be developed. Statistical properties of the resulting estimators will be derived and used in developing inference procedures.

Indexing (document details)
Advisor: Agustin, Zenia, Agustin, Marcus
Commitee: Chew, Song Foh, Pailden, Junvie
School: Southern Illinois University at Edwardsville
Department: Mathematics and Statistics
School Location: United States -- Illinois
Source: MAI 54/02M(E), Masters Abstracts International
Subjects: Statistics
Keywords: Lifetime distribution
Publication Number: 1571931
ISBN: 978-1-321-45233-4
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